Anxiety while Reading Social Theory

I have to admit I’m a shallow, and lazy reader. I prefer reading texts that are simple, and clear in prose. My most recent read that I cherished, and learned so much from was Ellen Pao’s memoir, Reset. The narrative is relatively linear. Everything is told in a chronological manner. Ellen Pao is a to-the-point storyteller. The messages are straightforward enough that I did not have to read the book twice to get any deeper meaning of life. The main message is that the tech industry has a deep structural problem in lacking diversity, and it has been paying only lip service to improve the situation. The solution is that VCs and tech CEOs should be agents of change, by creating and shaping inclusive organization policies and cultures.

Now I am in the process of writing my dissertation, I have bigger theoretical, and philosophical questions that require close readings of certain philosophical texts. There’s no reason why I should not set time aside to do these readings. I ought to read them at some point, and I have decided that now is the time for me to engage with social theory.

While contemplating about the different epistemological worlds that the left and the right in the United States are living in right now, I was recommended to read Black Feminist Thought by Patricia Hill Collins, and The Racial Contract by Charles Mills. I was elated at the challenge. Yet I have to admit that my anxiety and fear of philosophy, and social theory did give me some reservations about how much from the texts I would understand, appreciate, and be able to engage with.

Regardless, I am giving these texts a read, and will document my reactions toward them in the next few blog posts.

Production of culture

I am copy-ing this list as a reading list for cultural production.

Code and Culture

[Below is a recent list Peterson wrote outlining the production of culture perspective. You can view it as an update to his ARS with N Anand. Pete wrote it to accompany a talk he gave and circulated it to some friends. I copy-edited/tagged it and am posting it with permission. If you know links for any of the non-tagged citations email me or put them in the comments and I will update the post. –Gabriel]

| Richard A. Peterson |

Examples of works written in the spirit of the Production of Culture Perspective

Created for the working conference
Euro-Pop: The Production and Consumption of a European Culture
Villa Vigoni, Lake Como, Italy 9-10 June, 2009

Richard A. Peterson

A. The production of culture perspective focuses on the ways in which the content of symbolic elements of culture are shaped by the systems within which they are created, distributed, evaluated, taught…

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Red Pill Blue Pill by David Neiwert

David Neiwert examines “new conspiracism” in the age of Web 2.0, and how it is linked to online radicalization. Following are a few paragraphs about epistemological bubbles that have emerged on the Internet in the past 30 years:

Like the hypercool hero Neo in the films, true believers in the alternative universe of conspiracy theories are absolutely convinced that the epistemological bubble into which they have submerged themselves is the real reality.

The red-pill metaphor is a very provocative, and effective metaphor for people to be attracted to, and used when they transition to an epistemological bubble of the extreme right.

The universe of conspiracy theory constantly recruits new followers on the Internet. Somehow, this movement sounds like a spread of a new religious movement:

Sorting out good information from bad has become seemingly an overwhelming task in the age of the Internet and social media. Some people have stopped trying. Others have embraced the abyss, as it were, by diving into the epistemologically malleable and manipulable world of conspiracy theories, a zone where normative rules of evidence and factuality need not apply.

October Reading List

I thought that I would have read a lot during the month of September. It simply was not true. Reading is labor for an academic (more precisely for an aspiring academic). I finished reading half of the books in my September reading list, and was also able to write a summary of one book for my dissertation project. That was an accomplishment. Being engaged with a scholarly book in reading and writing is a very labor intensive activity. To keep the momentum going, I will be reading the following books in the month of October, or more like the remaining two weeks of October.

The books are organized around four themes: platform content moderation, racism, diversity in tech, and organization studies.

Dying of Whiteness

This books aims to examine:

how particular American notions of whiteness—notions shaped by politics and policies as well as by institutions, history, media, economics, and personal identities—threaten white well-being.

White Habitus – Racism without Racists

In his seminal book Racism without Racists (2006), Eduardo Bonilla-Silva defines the concept “white habitus” as “a racialized, uninterrupted socialization process that conditions and creates whites’ racial taste, perceptions, feelings, and emotions and their views on racial matters.” This concept explains certain idea of white solidarity, and white identity that I am currently trying to understand in the American context.

Bonilla-Silva goes on to explain: “One of the central consequences of the white habitus is that it promotes a sense of group belonging (a white culture of solidarity) and negative views about nonwhites.” Scholars often stay away from discussing the effects of active social isolation from ethnic minorities by white Americans. Bonilla-Silva doesn’t shy away from such a difficult topic. He points out that this kind of habitus develops a sense of identity, a sense of belonging, and a shared experience. Further exploration of white solidarity and identity in contemporary America under Trump is a difficult task. In the past two months of my reading on the subject, the book that deals the best with this topic is Dying of Whiteness by Jonathan Metzl.

September Reading List

I am not going out to restaurants, I also not using the subway to travel anywhere. The COVID-19 Pandemic has helped me save some money. I spent this ear-marked money on books. Because of work from home, and school’s work from home policies, access to physical books has become very limited to me. I don’t do well with e-books. Reading e-books does not help me retain information. Words come in and out immediately whenever I read things on my computer screen. I need to hold a physical book in order to think slowly what the author means.

Following is my reading list for the last 10 days of September: Dying of Whiteness by Jonathan Metzl, Red Pill, Blue Pill by David Neiwert, Talk of Love by Ann Swidler, Summoned by Iddo Tavory, and The Age of Surveillance Capitalism by Shoshana Zuboff. These books have been suggested to me by colleagues, friends, or advisors. They are fall broadly under three categories: whiteness studies, ethnography/cultural studies, and digital capitalism. I still read scholarly articles for information, and research. Yet when it comes to reading for critical engagement, research and pleasure, I still prefer books. I am not entirely sure my dissertation will turn into a book, but I cannot deny the appeal of having my name on a monograph published by an academic publisher. Let’s wait for a couple of years to see where and in what format I will end up publishing my research.

Book Review: Ghost Work

I have planned to read Ghost Work by Mary Gray and Siddharth Suri for a long time. I bought the book when I visited a talk by Mary Gray at Data and Society about a year ago. Since then the book still sits on my bookshelf. The general theme of the book is about the necessary unseen human labor behind the seamless automated systems. The core concept of the book is the idea “paradox of automation’s last mile.” It refers to the phenomenon whereby when Artificial Intelligence becomes more advanced, it would create “temporary labor markets” to solve “unforeseen and unpredictable tasks.” Furthermore, the grater paradox of automation is that “the desire to eliminate human labor always generate new tasks for humans.” In other words, automation cannot and would not in a foreseeable future, rather automation reconfigures work, and reorganizes human input in the production process.

In the authors’ own words, on-demand service work is necessary because we do not know when machines need human input:

“As machines get more powerful and algorithms take over more and more problems, we know from past advances in natural language processing and image recognition that industries will continue to identify new problems to tackle. Thus, there is an ever moving frontier between what machines can and cannot solve. We call this the paradox of automation’s last mile: as machine progress, the opportunity to automate something else appears on the horizon. This process constantly repeats, resulting in the expansion of automation through the perpetual creation and destruction of labor markets for new types of human labor. In other words, as machines solve more and more problems, we continue to identify needs for augmenting rather than replacing human effort. This paradox explains why on-demand services – commercial ventures that combine humans and APIs to source, schedule, and deliver access to goods and services – are more likely to dominate the future of work than AI and bots alone (p.176).

The authors interview workers in the United States and India, and bring them to us. They go behind the API curtain, and reveal to us who the workers are, what are their aspirations, and why they work for on demand platforms. This book is comparative on many levels. First, it compares workers in different countries: The US. and India. Second it compares experiences of workers who work for multiple platforms: Amazon Mechanical Turk, Microsoft Internal On-Demand platform, Amara translation service, and LeadGenius. The diversity of platforms, and countries allow us to see a picture of an emerging global on-demand labor market, which performs million of tasks, which vary in complexity. This book therefore enables us to see what is often hidden and abstract.

The authors then provide institutional background on why the on-demand labor market has become necessary in the digital revolution. They also show us how on-demand labor market is not a new system. Before the industrial revolution, many women and households took on the job of sewing the last buttons to clothes before the textile industry figured out how to automate the process, and confined the work within the walls of garment companies. This inclusion of non-institutional labor is important in the process of automation.

As they walk us through lived experiences of their interview subjects, the reader recognizes heterogeneity of human labors in this on-demand market. What becomes apparent is that since the market does not have a clear requirement of educational background, training level, etc, it allows for a diverse labor force with different levels of training, different levels of education, and coming from diverse racial, ethic, and religious backgrounds. However, this heterogeneity of labor supply, and diverse forms of tasks also create inefficiency, and friction because workers have different levels of skills, and that requesters/ employers have to define the tasks themselves. The authors show that this system involves a lot of transaction costs for both workers and employers. The two sides have to put in the time to find the right match, and to explain to each side how to do the task as intended. Workers avoid the problem of looking for tasks by creating social networks outside of the platform. They rely on social media, online forums to find the right tasks. As the author outlines this problem of transaction costs, I wonder whether building a well thought-out communication platforms for on-demand workers and employers would be a potential solution for the various transaction cost problem in this market. This is a technical solution for the current inefficiencies in this market.

One theme that I observe in this book with other Gig economy books that I have read in the past year is that workers in this economy are subject to algorithmic arbitrariness. Workers are suspended, and kicked out of the platforms sometimes randomly, and sometimes according to rules that are not taking their real life situations into account, while workers have no recourse, no where to complain. This shows the power of platforms over workers, and that workers though important to platforms’ profitability are not treated as assets but expandable number that could be eliminated at will.

Gray and Suri explain:

“The worst expression of algorithmic cruelty is disenfranchisement. Under the guise of safety, systems designers make it easy to block or remove an account in case a bad actor tries to cheat the system. This adversarial stance means that good workers are sometimes misinterpreted as shady players. Inevitably, mistakes are made. A worker changes an address, loses her internet connection, or shares an IP address with another worker. Each one of these things is potential red flag. The algorithmic system sees the flag as a possible security threat and, with no one at the helm to distinguish friend from foe, the worker is penalized. The penalty may look like being blocked or suspended, or having an account deactivated. Again, in an ecosystem in which workers are seen as interchangeable, the system automatically eliminates what it deems bad apples. The sad irony is that even the best – intentioned and most seasoned workers can get caught in the dragnet.” 86

Workers are dehumanized through the process of de-identification. Mturkers become lists of numbers. This reminds me of how Jewish prisoners given a number during the Holocaust. Giving a working human being a code to interact with is so dehumanizing for both sides: the requesters, and the Mturkers. The authors though qualify this statement by saying that in case of workers who come from discriminated classes (gender, religion, etc), not being identified by names and gender sometimes giving them advantage.

At the end, I feel that the book presents a good narrative of what is going on in the tech economy. However, as a sociologist of work, one question remains unanswered is the question of “work process” among on-demand gig workers: Why do they work so hard for very little paid, and why don’t they quit? What is the average tenure of an on-demand gig worker working for an on-demand platform? The authors point out the 80/20 Pareto rule to create a typology of three group of workers. However, I want to know among those who make on-demand work their full time career, why do they work so hard for little pay? Another question is why they not call them gig workers? What is then the difference between gig work and on-demand work? Aren’t they the same?

To answer the question what keeps they in the game, the authors provide a partial answer: many of them are in the game for the cognitive benefit of it. They learn new things, keep up their skills (most of these answers come from Indian subjects). However, my sense is that because the book is not an ethnographic research, they can never quite get at the process that workers rationalize the decision to remain in an exploitative labor scheme.

Besides, How about their American counterparts? Why are they working so hard for little pay? The answers are either implicit or not satisfactory. Implicit in the sense that they work for various reasons. One, the workers population are so heterogeneous, they should have different reasons why they work in this sector. Thus, they should also have different reasons why they stay. Is there anything about the on-demand aspect of this that keeps them stay? Is there anything about the brandname (Amazon.com, or Microsoft) that make them stay? These questions remain open.

Finally, as a methodology enthusiast, I feel the book to be not transparent in its methodology. Who were involved in the interviewing process, who was contacted, who was doing the interview, etc. These pieces of information is absent. As mentioned earlier, because the book is not explicit in whether ethnography was involved at all, readers cannot really picture the embodiment aspect of online/on-demand work.

Because I care so much about reproducibility of research, the book does not have a methodological appendix that makes me cringe. I know that it is produced for popular audience, but as a scholar, a researcher, a scientist, I want to know how many people they have interviewed, how did they interview them, how many in person, how many remote. How did they avoid positionality biases being MSR employers, privileged, and at times employers of those ghost workers.

Overall, I agree with the authors that there’s a global ghost work sector that is increasing in size because of the increase in demand for human in the loop tasks from various tech companies. They are working outside of the formal employment structure, and they are subject to the whim of the platforms, and being exploited by requesters because of the platform design. However, I think the book has not answered many questions, and one of which is methodological, and another is theoretical.

Despite many questions that I have, the book is a starting point of a long over-due conversation: who are the human workers who power machines. How can we as society protect them, and enable their creativity for our better future. The book is both practical, and hopeful that we actually will continue to need humans in the loop. The book also provides one practical solution for job training program at the city level that I really like: supporting public education, and letting residents to take college classes that they would want to take in order to benefit their work. This similar program enabled me to audit courses at Humboldt University, Free University and Goettingen University during my stay in Germany. It plugged me into the intellectual environments of those excellent public universities, and through those courses I had also made long lasting friendships. I’m all for investing in public universities and making their courses available to those who pay their taxes to support such excellent public education.

Book review: After the Gig

This semester, I am teaching the class The Sociology of the Gig Economy at Hunter College. This is a master’s level class where graduate students in social science research, and honors undergraduate students will explore various issues of the gig economy. I am pretty excited about the content of the class. After our first meeting last week, I have become even more excited about the participants. Throughout the semester, students and I will engage in a few public pedagogy projects whereby we produce content and knowledge for public consumption. This is my first time experimenting with such an idea. I think there will be challenges, but hopefully we’ll be able to create solid content for public consumption.

In the process of preparing for the class, I have ordered like 20 different new books in the summer. Most recently I finished reading the book After the Gig by Juliet Schor. As the name suggests, it is a book about the gig economy.

I categorize this book as an empirical examination of the gig economy from the sharing economy point of view. This book is on my bookshelf physically placed next to Uberland by Alex Rosenblat, and Hustle and Gig by Alexandrea Ravenelle. I have reviewed Uberland for Sociological Forum, and really appreciated the book’s approachable language. Alex Rosenblat does not use heavy theoretical language to make her point across. That is Uber drivers come from a diverse backgrounds, who have different reasons why they become taxi drivers. Yet she’s able to show that over time, Uber has engaged in shady practices to increase surveillance and control over its workers, its customers, and critics like herself. When it comes to Hustle and Gig, I appreciate Ravenelle’s clear argument: that is, in the gig economy, companies shift risks onto workers. And her solution to this risk shifting problem is to advocate for changes in the independent contractor category. The government needs to make gig companies recognize these workers as their workers. So instead of getting a 1099 form, these workers should get a W2 form like other “organization men” in William Whyte’s words.

How is After the Gig different from the other two gig economy books that were also published by University of California Press? I think the answer has to do with its approach, scope, and the consumption aspect.

First, Juliet Schor approached the gig economy phenomenon from the sharing economy point of view. That is, she used the consumption, anti-capitalist discourse of the gig/platform economy as the spring board. For example, throughout the book the idealist discourse is being problematized. This discourse makes the argument that the sharing economy promotes collaborative consumption, environmental conservation, and financial independence. While the other books I mentioned above focus exclusively on the workers and how platforms use data and algorithms to discipline workers, this book looks at other aspects of the platform economy: collaborative consumption, environmental conservation and then economic gains for workers.

Second, this book relies on data collected by a team of researchers that look at many for profit and non-profit platforms. This is a marked research design difference from the other two research projects. Trained as an economist, Juliet Schor is able to show the reader what the economics of the platforms is. I really appreciate her non-jargon explanation of how economics works in this economy. In order to keep workers poor and dependent on platforms, Schor argues that we need to understand two important concepts: algorithmic control and policies of precarity.

What is algorithmic control?

To some extent, algorithms are self-learning entities that change without human intervention. But on labor platforms they are also paired with policy decisions made by real people.

In other words, platforms use both automation (algorithms), and policy decision making to discipline workers. While it takes almost nothing to start on any platform (Uber, Taskrabbit), platforms can fire workers anytime (through deactivation mechanism). This high cost of job loss is really high for gig workers.

Schor and her team argue that “platforms have ushered in fundamental changes in the organization of work.” They are parasites, who do not pay tax, and just use public resources (roads, etc). They subsidize consumers through venture capital money, and then compete with public services (public transportations).

Similar to what Alex Rosenblat’s argued in her book, Schor also argues that the platform economy has ushered in a new labor regime. Specifically, we observe a retreat from control, or direct-human control. Employers allow for a wide range of work hours, a wide range of workers with different educational backgrounds, etc. Similar to historian Louis Hyman, and communications scholar Mary Gray, Schor also highlights the similarity between this system and the pre-factory era home-based “putting out” system. Platforms as accepting more heterogeneity among its workers allow for a more diverse workforce. Yet, this also means that we’re facing with more inequality within this economy.

Finally, Schor examines a few case studies of non-profit sharing platforms, and shows the readers why they fail, and how they fail. She argues that sometime the setup lacks “a value proposition” and operates based on “ideological commitment.” In other words, their economic activities appear to be not durable, and would soon fail when economic situations change, and other social dynamics (such as status positioning) kick in.

In conclusion, Schor documents the rise of commercial platforms, and attributes their growth to the fact that they have offered something of significant value to users: consumers get lower prices, and providers get extra income with flexibility. However, looking at consumers and providers alone is not enough. The platforms have plenty to gain from these activities such as power, and consumers’ data. Thus Schor calls for more regulations in this market in order to protect consumers, providers, and society as a whole.

Baking and Culture of Measurement

I have been obsessed with baking Asian cakes such as mooncakes, anpan, Hokkaido bread lately. My tiny New York City apartment kitchen has been filled with baking ingredients and tools including five different types of flour, different molds for different cakes and bread. The basic equipment and ingredients are readily available in my home.

However when I started making mooncakes for example, I ran into the problem of recipes. In order to get a hang of baking techniques, I often go to Youtube, and observe how other people from different countries make mooncakes, and Hokkaido bread. Once I read a few blog posts, and watch a few videos, I seem to get a conceptual hang of the workflow, and feel that I can comfortably make a new type of bread without much difficulty. However, people often say that baking is a science. That means, what determines whether a cake is a success or not lies in the precise measurement. This I found to be a troubling issue especially when making Vietnamese cakes.

I found recipes in Vietnamese on the Internet to be very underwhelming. Most of the time, the measurements are not precise, which throw me off. Whenever I found a ciabatta recipe for example, the instruction is full with details that I feel happy about actually not reading the extra story that the writer tags along to personalize the food making experience. I would go straight to the end of the blog post, look at the recipe, get a general idea of the workflow, then I would go to Youtube and find videos to see how the recipe actually is executed, and certain steps that could never be verbalized in writing.

This general workflow helps me with many cuisines: Chinese, German, American, Mexican and Mediterranean. But when it comes to Vietnamese food particularly Vietnamese recipes that I remember as kid growing up in Vietnam, I find lots of frustration. I often find the writing to be dry, not detailed enough, and it leaves me with an unsatisfactory feeling that the author does not try to make sure that I’d be able to re-create the same experience. This realization made me think about a culture of writing cookbooks, recipes, and blogs. Each recipe takes a lot of care to master, and then to write a blog post to explain what one does. This is a lot of labor and care. What sets the Vietnamese recipes and Western cuisines recipes apart for me now is this level of care, level of appreciation.

I believe that there are many Vietnamese recipes out there that people need to try. Yet, in order to figure out what they are, one needs a class of cultural producers who would be able to introduce these different recipes online, and then popularize it in the world. This is such a cool idea for a Youtube channel, and food blog. I hope that a class of young talented Vietnamese people out there are doing precisely this: to make sure that Vietnamese recipes are accessible to the culinary world, and treat Vietnamese foods with care, and patience.

Topic Modeling makes Bayesian Cool

I have been obsessed with topic modeling for more than a year now. It is an NLP technique that actually has important applications in social science research. This is a big feast for computational methods, and for a social scientist like me.

When I first learned about topic modeling, I spent a lot of time trying to learn how to make it work. Besides, I also wanted to know how I can use this cool technique in my research concerning race/ethnicity, immigration, etc. I was not concerned at all about the mathematical underpinning of the method.

This all went well until I learned Bayesian statistics this summer. Now I see Bayesian everywhere. I finally understand that under the hood, Bayesian inference makes topic modeling such as LDA, or STM possible. This eureka moment really elated me.

It turns out that I have been using language of tuning hyper parameters without really understanding what goes underneath the entire process. Now with some basic Bayesian statistics, things start to make more sense to me, and I feel more confident in explaining how topic modeling works.

Baking is a science

People say baking is a science, and cooking is an art. I enjoy baking much more than cooking because oftentimes there are precise description, and precise measurement of how much ingredients and materials one should prepare before making a cake. Until I tried to make moon cakes, a type of cakes that many East Asian countries eat during the Moon Festival. It’s my childhood favorite, and I miss eating the kind that one can only find in Vietnam (bánh thập cẩm, or mixed flavor).

I followed a few recipes found on the Internet and Youtube. Results have turned out to be dried, and not so pretty.

Then I tried my hands in making mochi ice cream. It’s even more difficult.

Mochi Ice Cream - Kirbie's Cravings
Picture: Kirbie’s cravings

What I figured out during the two failed experiments is that making Asian cakes is so much more complicated that I had thought. I expected that unlike making a croissant or tarte tatin, I at least have an idea how they should taste like at the end. As a born and raised Vietnamese, at least I have the moral authority to say that the cake I make taste like what Vietnamese people in general would consider good. What I recognized at the end though making these cakes has less to do with measurements, ingredients. It has a lot more to do with techniques, equipments, and whether one has a clear expectation how the final products should taste like. So in many ways, baking is also an art. Making these cakes is more like cooking a bowl of Pho than making a tres leches cake.

These Asian goodies are supposed to be moist, soft, and delicate. They are not supposed to be chewy or fluffy. They cannot be made using a ready made cake mix. They take a lot of time to make, and the process is pretty involved. One cannot cut corner and expect the output to be pretty or tasty.

This baking process reminds me of the scientific endeavor that I am engaging in at this moment. When one embarks in a research project, one thinks that they have a clear idea what to do, until they figure out that there are many steps in between. Then they become confused, and frustrated. The science of baking, and making pastry is not opaque especially in the Internet era where many recipes are available for consultation. The opaque part lies in the details how one should mix what kind of flour, and which one goes into the oven first, and how much egg coating should one put on top of the delicate almost ready mooncake.

These baking experiments made me realize that in doing any project, patience is key, and that figuring out the perfect procedure takes many trials and errors. Translating it to doing science, maybe writing papers over and over again helps one write better papers. Maybe having one solid idea and then translating it to written words would eventually become easy once I figure out how to not cut corner?

Applications of Bayesian Thinking

I struggled with understanding how to use Bayesian statistics in my professional work. More specifically, I am struggling understanding the building blocks of Bayesian statistics. What I do see is that Bayesian statistics involves probabilistic thinking, and very clever sampling of data distribution. On the higher level conceptualization, the ideas of prior belief, and updating your belief to get a posterior estimation are intuitively appealing. However, when it comes to mechanics of applying Bayesian logics, I am struggling a lot.

This struggle does not deter me from enjoying reading about Bayesian logics being applied in real life situations. Recently I listened to a Data Skeptic podcast episode about data representations, data visualization, and how we citizens or audience are unconsciously being educated about statistics through reading and interacting with very well-thought out work of data journalists and data scientists at news organizations. The specific example that professor Jessica Hullman mentioned is an example from the New York Times’ interactive graphic representations of inequality in America. The interactive exercise asks the reader to provide their prior belief about inequality in America, and then presenting them with data, thus nudging them toward updating their belief. This is such a brilliant statistics exercise from a very well-respected news organization in the US. I wish that more news organizations in the world exercise what the New York Times does: using data journalism to educate the public about social issues in a scientific way.

For those who would want to listen to the podcast episode, it could be found here. Let me know what you think about Bayesian statistics, and how one can implement Bayesian statistics in social sciences.

What Journal to Publish in?

My mentor often says that before submitting a paper for publication to a journal, one has to do thorough “market research,” or to have a general understanding of what the journal is about. My understanding is that each journal is a cultural institution, and the job of a researcher is to make explicit those cultural norms. Relying on this explicit knowledge, they could make a more informed decision about the venue.

A friend came to me today with a set of related questions:

Where does one look to find out simply what the background of a journal is — which discipline(s) it covers, how long it’s been around, what its mission is?

I thought about these questions for a while, and came up with a 6-step procedure to figure out how one should categorize a journal:

  1. Read the journal’s self-description
  2. Read the Wikipedia’s page of the journal
  3. Examine the chief editor’s profile. The chief editor’s background is indicative of who the potential authors and the audience should be.
  4. Examine a few articles, and see who are the authors
  5. Use the advanced search function on Google scholar, and find articles published in the journal, read the articles titles published by the journal.
  6. When the journal is interdisciplinary, look at a few issues to see which disciplines the authors come from.

This might be different from how other academics do their “market research.” I’d be interested in learning more about how other people decide where they submit their work, and why they make such decision.

Bayesian Struggle

Bayesian Fun
Picture credit: GA Tech

I am currently attending a statistics summer school at ICPSR (University of Michigan), one of the most renown methods training grounds for social scientists. I had applied to the summer program before, but never participated because I could not afford it, and that I did not really want to go to Ann Arbor in the summer. But this year, amidst the Covid19 Pandemic, ICPSR became a possibility at least financially, and also due to its online format I never have to go anywhere outside of my apartment to attend it.

My experience has been great so far. I’ve got to meet with really smart and self-driven PhD students, researchers, and professors from all over the world. This is really exciting. We have been doing trivia on Zoom, swapping tips, tricks and talking about each other research interests on Slack.

My enthusiasm to learn more stats got curbed immediately when the Bayesian statistics class started. The reason that I signed up for the class was simply that I’m interested, and I want to know more about probability, which I never formally learned as an undergraduate student, and is currently not offered in my graduate program. I soon recognized though that the class has a lot of formal mathematical proofs, and probabilistic theories, and math axioms, something that I missed doing, yet my math knowledge not quite sufficient to do abstract derivatives. I forgot most of my linear algebra, and differential equations after almost a decade doing ethnographic work, and reading social theory.

The class started from the simply and elegant Bayesian theorem:

Use Bayes' Theorem to Investigate Food Allergies — Count Bayesie
Photo credit: http://www.countbayesie.com

It then became a full length discussion on how to use different priors, different sampling techniques, and how clever mathematical manipulation can get you very far. My head is been spinning, and I feel seriously doubtful of my intellectual ability.

One good thing that comes out of this experience is that I have been reading a lot more because Bayesian logics does not appear intuitive to me. I’ve been watching a lot of Youtube videos about Bayesian applications. I am curious at what point this world view would make sense to me.

To get a sense of what this Bayesian world feels like, and thinks like, I watched this funny, and engaging YouTube video:

The presenter makes it feel so easy. She naturally incorporates concepts such as conditional probability of A given B, and the probability of A, or of B in her speech. It feels as though she lives her life in a Bayesian way, and thinks like a Bayesian. Then she provides example of how a person would be able to use the Bayesian theorem to calculate the probability that their blind date would share their interest in Star Wars given what they already knew about the world. This sounds very nerdy, but it works for some people. I wonder how many people actually think like this. Certainly I am not one, and I am also not surrounded by Bayesian thinkers on a daily basis.

Ok this video makes Bayesian interesting, and applicable in real life. How about moving a little bit further? I have not been able to understand all the assumptions, and sampling techniques in doing Bayesian statistics, but probably I can ask relevant questions that highly technical people could answer. The whirlwind of deep learning seems to be sweeping every corner of the scientific world, how do Bayesian statisticians, and applied Bayesian people survive and adapt? I found that Bayesian people are making themselves relevant, and pitching their work to the deep learning and machine learning communities. For example, most recently at NeurIPS 2019, one of the most important machine learning conferences, there was a workshop called Bayesian Deep Learning, where presenters and speakers pitched various ideas about how Bayesian statistics is relevant to machine learning, and vice versa. This is very exciting. So Bayesian statistics is not a dying field that I’m stumbling into now. It’s evolving as the field of statistics is getting more and more exciting.

I still have a lot to learn during this summer program. It feels very bizarre to go back to do derivatives, and doing matrix algebra. Yet, I am excited about learning new things. Math always makes my brain hurt. But like one of my math professors often said: “Doing math is joyful thinking.” I should enjoy this process of writing and following proofs. Sometimes I even wondered had I remained doing math since college, what would I have become?

Deep Listening: Engaging with Respect

When I first started college in the United States, I struggled. I struggled with English because as a non-native speaker, the first year was very difficult. Every student had to take English 101, first year seminar, major, and minor required classes. Even before school started, the incoming freshmen were asked to read a non-fiction book, and created original and innovative responses to it. I was overwhelmed. Nobody had ever taught me how to react to a non-fiction book. What was expected of me? How would the deliverable look like? I performed well if there’s a clear guideline of what deliverable I should provide. But when the deliverable is anything possible, I became paralyzed.

I arrived in college with the feeling that I was insufficient because I could not produce a creative response to a non-fiction book. Then in the first orientation week, I saw my peer products displayed at the fine arts department, I felt both awed by what they were able to create, and felt inadequate because I was not creative, and that I failed to bring with me any artifact. I was trying to figure out the American college system, and American higher education culture.

Then English 101, a required class, started. I was both excited, but nervous, and sometimes dreaded that I had to go to English classes. As a high school student, I never excelled in English, or Vietnamese. I never got good grades in these subjects, or felt the urge to write any poem, or wrote a good literary analysis. My high school writing was mediocre but logical. I often got away with writing a very dry essay that hit all the points instead of writing a flowery essay that makes the reader feel good. I kept the same attitude toward English, or maybe the fear of humanities subjects when college started. My English professor also looked very strict, and the readings were very foreign to me! We read Othello, old English poems, and Tony Morrison’s Beloved. I had virtually no cultural background to be able to comprehend the texts. My only tool was to pretend that literature speaks to all humanity regardless of the reader’s race, ethnicity, cultural background and lived experiences. Later on, I learned that this assumption was very wrong.

English 101 was the class that took most of my time, yet I felt really inadequate in it most of the time. Until one day, I had to make a presentation about a reading in class. I don’t remember what the presentation about any more. The only thing I remember now is that it was a 10-minute presentation about an author, and their work. My job was to summarize the author’s life, and their literary works. The only and the most important thing I remember though is the feeling that I had during and after the presentation. My peers were listening to me very attentively, and asked questions after I presented. I was of course nervous, but they were all paying attention to me, my powerpoint, and did not care much about my broken English. I felt empowered. I felt respected. I felt engaged. It was definitely the first time that I recognized the power of being listened to. My expectation was that nobody would listen to my presentation because I did not really know what I was doing. I also never took English seriously. Yet the fact that my peers and my professor took me, the topic and the subject matter seriously, I felt elated.

That moment of feeling respected, recognized, and centered was decidedly a turning point in my approach toward higher learning. It was also the moment when I recognized how empowering it could be for a speaker to be able to summon his/her audience’s attention.

In this blog post, I am arguing that when one engages in deep listening, or paying attention to the interlocutor with empathy and appreciation, one gives agency to one’s interlocutor by giving them respect.

As human beings, we all want to be treated with respect. It’s an instinctive desire. I had such a low expectation of how my peers would treat me in an English class, thus when I was treated with respect, I felt elated, happy, and empowered. What if we use the same practice for doing research? What if deep listening as a way to show respect to a research subject is a principle in doing qualitative research?

During the Covid-19 Pandemic, everything has been moved online. Now everyone knows what Zoom is, and conducting research interviews has become so much easier than before because teleconferencing has become normalized as a social practice. My argument is that in the 21st century, where more activities are conducted online, sociologists should also conduct their research online. I think that conducting interviews online should become a part of interviewing methods. It should be in one’s research repertoire, in one’s tool box. This research environment is not ideal for a lot of projects. However, as researchers we should make do with what we have.

In the current situation, when researchers interview participants online, we need to practice deep listening, and pay attention to it more than ever. What does it mean? It means letting subjects sufficient time and care to elaborate on their points, and giving them virtual space to feel comfortable. I think psychologists have done this very well when we all transitioned online. Now all psychotherapists are offering online therapy. They use virtual spaces very well. They use virtual platforms to elicit deep emotions, deep connections, and deep openness with their subjects. Sociologists should learn this deep virtual listening practice from them.

What constitutes deep listening then? There are three basic components of virtual deep listening: (1) establishing virtual rapport, (2) maintaining eye contact and attention, (3) asking follow-up questions.

Establishing virtual rapport: Establishing quick rapport to any person is an art. A great field worker often incorporates humor, and the ability to relate to the interlocutor in the first five minutes of interaction with a new interview subject. Establishing a virtual rapport presents a challenge because the interviewer is no longer being physically in the same place as their interviewee. This physical distance creates a challenge because relating to somebody virtually is a very different skill than relating to someone in the same physical space. It seems that podcasters have figured out how to establish quick rapport with their interlocutors very quickly. I would love to know how they do this. What are some tips, and what should one pay attention to?

Maintaining eye contact and attention: this is true when a researcher interview some one physically. It is even more true when an interview is done virtually. Maintaining eye contact via Zoom is very difficult. Sometime we do not know whether we are looking directly at the other person in the eye. This act of staring at a screen for too long might lead to Zoom fatique, the feeling of tiredness, anxiousness or worry with yet another video call. Yet in order to get the best interaction, and that to help the interviewee to come forth with their life stories, paying attention to what being said, and how they say it is utmost important. Paying attention to details is always the best working guideline.

Asking follow-up questions: As I interviewed podcasters for a research on the podcasting industry, I learned that not everyone is a good podcaster because they do not know how to ask follow-up questions. This point relates to the previous point about paying attention to details. I have the habit of taking detailed notes when people talk. It’s a very good practice to get things visually in front of you when you want to know what is being said. Many a times, I used my notes to come back to points that the interviewee said, and I needed more elaboration. A superb fieldworker does not take detailed notes. They only need to take mental notes, and write down very short notes. Then when they go home, they will fill in the blank what is missing from their notes. This is a great mental exercise. I strongly believe that a good fieldworker has very good memory. I am often afraid of losing track of the conversation, thus I take notes of everything. Remember asking follow-up questions for further elaboration is always helpful when the interviewee talks about a social concept using their own words, and to construct their social life through their own lens.

In conclusion, deep listening is an important practice for everyone in this busy world where technology makes us more isolated than ever. For a researcher, deep listening helps us connect with research subjects because it is a way for us to give our interviewees respect. In the context of virtualizing research, deep listening is even more needed because it can help us to bring down the physical distance of a Zoom call. All in all, I would encourage everyone to think about different ways in which deep listening could be practiced, and how it is being applied in different contexts.

Audm vs. Diversity in the Age of #BlackLivesMatter

While America is experiencing a social revolution lead by Black Live Matters activists, every individual, every institution is forced to pay attention to the question of diversity, inequality. At the same time, as I am reading news coming from different sources about Covid19, and social justice, I feel that I appreciate the good work that journalists do. I read about the troubles that journalists of color are going through. Newsrooms across the nation are grappling with the racial inequality conversation that the nation is having. I want to support their work, especially supporting good works by journalists of color.

Then I found Audm, an app that reads high quality news articles aloud. The company has recently acquired by the New York Times. Some observers have said that this acquisition marked a turning point in the New York Times’s approach to audio content, and audio production. The New York Times has beefed up its audio content production. Its the Daily podcast is one of the most popular podcasts in the world. The news organization is now behaving more like a tech company than a newspaper company. Its Data Science department is staffed with some of the most well-known data scientists in the world. Its constant acquisition of startups makes it looks like Amazon, a website of everything. I wonder at what point all of my news source would come from some organization that is associated with the New York Times.

At first, I rejoiced at the idea that now I can listen to the highest news content by a very cool app. It felt authentic, and intimate like listening to a podcast. At the same time you’ll get to know the most important information out there written by the best journalists in the industry. Then after having listened to a few articles, I found one pattern: all of my news is read by white men even when the news was written by a brilliant writer of color, or a female writer of color. This does not sound right to me. Instead of giving power to the writer, curating some of the most important content to readers, the app and its voice over staffs reproduce a type of “audible inequality” in the voice over industry. If there’s diversity of writers among New York Times staffs, I’d want to also have diversity in voice over actors.

Even when second generation Asian Americans born and raised on American soil, they have a distinct voice that is different from a middle age white man’s voice. For example, a Vietnamese young writer would have a voice that has been nourished by their migrant parents who came to the US, overwhelmingly in the aftermath of the Vietnam War. This person has been raised within a community that is still grappling with the idea that they are now a minority group in an increasingly diverse society. The young writer has been nourished with fish sauce, and Pho, and a history of the Vietnam War, and growing up being told a model minority student. The voice that this young individual produces is representative of all of those lived experiences. It is unique and distinct. I want to listen to an article written by a Vietnamese talented journalist, being read by a talented Vietnamese voice over actor. In that process, an intellectual work (the article) benefits two knowledge workers (the writer, and the voiceover actor) of color.

What is happening now is that the writer of color does the difficult work of producing a piece of intellectual work (the article), and it is read by a white middle age actor, who benefits from the first person’s work, and reproducing the stereotype that only white voice actors are talented because their voices are featured. This reality incurs symbolic violence on the talented writer, and reinforcing existing income and racial inequality that upholds the current economic structure. When the audience does not critically think about what they listen, they gradually acquire an association that there’s no talented voice actor of color out there. This is especially damaging for young people of color who would dare not go into a field like voice over because they never saw any people like them in the field.

To conclude, I suggest that Audm, and by extension the New York Times, should diversify its cast of voice actors. If an article is written by a writer of color, it should be read by a voice actor of color. On a broader scale, the audio industry itself should diversify. There are plenty of opportunities for voice actors of color to contribute, they should be given roles and opportunities where appropriate. As of now, I will not subscribe to Audm. I don’t think my money would be well spent here. I would rather read the article written by the talented writers of color, and imagined how they would sound in my head rather than listening to the app, whose voices do not represent the real writers. And then donate money directly to an artist of color on Patreon, where I know for sure that I directly contribute to their creative work.

Attention Economy 101

I am trying to figure out the concept attention economy, its genealogy, and how I can apply it in the contemporary media landscape. My first step was to check Google n-gram to see when the concept most in vogue. Here is what I found:

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This graph basically suggests that the concept was used a lot in Google books between around 1995 to 2013. It was most used around probably 2004. Then the frequency reduced.

The same diagram is rendered a bit differently when I chose to smooth out over the period of one book.

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This figure shows two peaks: possibly 2003, and 2007, after which point the mentioning of the phrase “attention economy” gradually dies down.

Now let turn to Google Trends to see how and whether this phrase shows up

This Google search term mirrors the Google Book results. I think the only difference is that Google trends are search terms floating on the internet, while Google ngram reviewer reflects the term being mentioned in books.

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This figure shows that the term “attention economy” was used a lot between 2004 (the year Google Trends started documenting terms I guess) and 2008. Then the interest in the term died down. The number seems to pick up a bit since 2018 until now, but it does not look significant.

If you compare the term “attention economy” with “attention” only, the result is pretty revealing:

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The red line represents the search result for “attention,” and the barely recognizable blue line represents result for “attention economy.” The overall trend for “attention” seems to go up a bit, while the trend for “attention economy” is almost zero. This is weird. I wonder why people no longer use the term “attention economy.” Does it mean it is out of vogue? Sometimes a term is defined, and then being criticized for not being able to capture a certain phenomenon, then it completely disappears from our linguistic circulation.

According to Wikipedia:

Attention economics is an approach to the management of information that treats human attention as a scarce commodity, and applies economic theory to solve various information management problems. Put simply by Matthew Crawford, “Attention is a resource—a person has only so much of it.”

This concept should be understood within the context of the digital economy and the information economy because only when there is a flood of information that attention becomes a rare commodity. And since information is so cheap to come by, companies such as Facebook, Twitter, and other platform companies are designing software, and platforms intentionally with the idea that attention is rare, and that they should design interfaces that capture the most attention (measured by how many minutes or seconds a persons spend scrolling on their platforms).

This concept clearly came from economics, and being applied to different economics-related fields such as marketing, management, user research. As a sociologist, I need to ask, so how are social relations formed, sustained, and reproduced in this economy? What are some characteristics or attributes of this economy should I pay attention to? Is an attention economy on Youtube different from an attention economy on Tiktok, on Twitch, and other platforms. How does it work differently on Instagram than on Twitter? What are some advantages and disadvantages of this economy to content creators, and their audience? How does this concept illuminate the podcasting phenomenon that I am examining?

There are lots to be said, and examined here. I am excited about the concept, and I am looking forward to learning more about it, and how to use it in my future work.

Life After a Manuscript Submission: Freeing Mental Space

Last week I submitted in a blog post manuscript for a center that I’ll be affiliated with in the next two years. Once the blog post was submitted, I felt very good about myself. I felt that I could start investing my time on something else such as writing posts for my own blog. During the writing process, I imagined what my life after the submission of the manuscript could look like. I dreamed that I could spend more time watching Netflix. I imagined that I would be more productive writing my personal reflections. I imagined that I would spend more time reading, and writing for other “important” research. I imagined publishing research articles.

Now the manuscript was submitted, I felt a sense of relief, but I still have not picked up anything that I thought I would do yet. I have another blog post to write for a well known public-facing blog in my discipline. I am slowly but cheerfully moving on to the next publication projects. My mentor once made a remark that writing momentum is what I am looking for. Once I get in the flow, I would be able to produce writing regularly. Every publication is in and of itself a project that takes a lot of brainstorming, writing, editing, and revising work. However, I feel like I have figured out the process, and that I am onto the next big thing in my life after each piece is turned in, getting comments, and suggestions from editors. I think I am gradually getting into this publication flow.

Once a manuscript is submitted, I feel confident about my ability to write, and that I have things to say. My mind is looking for the next challenge that I should engage in. Today, I emailed another editor about a new manuscript that will be due by the end of the month. They responded immediately. They were responsive probably because I have submitted a manuscript to them before. Now I am stacking projects on my plate. “One project in, another project out” is my current modus operandi.

I figure out that my work flow for each writing project includes (1) coming up with an idea (2) figuring out a theoretical framework (3) collecting thoughts, evidence, documents, arguments, (4) talking to friends, colleagues about my ideas, and the direction of the essay (5) coming up with counter-arguments to see how I can improve my writing even further.

For example, for the blog post that I am hoping to send out by the end of this week, I am still collecting data. I have written at least half of the post to figure out what I am thinking. I really practice the idea “I am writing myself into knowing.” Having the first draft done is always the most challenging. Once it is done, I can strengthen it by adding or dropping certain arguments, and/or evidence. My essay is half done now, and I feel good about the progress at least. My goal for today is to dust off the first draft, take a look at it, develop it a bit more, and send it out to get immediate feedback from my writing partners.

In the process of writing the above-mentioned piece, I recognize that I am not yet a fast writer. I am not yet at the level where I can produce an op-ed for a newspaper in less than a week. My writing often takes somewhere between two weeks to a month. Once I submit these hypothetical manuscripts, they are no longer topical. The world has moved on to new issues, new social phenomena. The writing process also takes a lot of emotional and mental energies. It is exhausting to write about current events as well because we’re still living them. Our minds are still trying to figure out what is the meaning of what has just happened. Sometimes, I feel being distanced from an event might help with comprehending it. Yet, if I give myself time to think about an event, and write about it, maybe I’ll understand it a bit more, and I will also help other people understand it through my writing.

As writers, scholars have words to express their thoughts and arguments to the world. However, being too slow of a writer might hurt their chance of having their ideas heard because if they are too slow, the world has moved on from the issue that they write about. Timeliness is key in writing as well as in other areas of life. It’s a misconception that academics and intellectuals have all time in their lives to think about the world, and carefully craft each sentence. Writing has a lot of hidden pressure, and anxiety. In the digital age, producing timely work is more important than ever.

Following are a few guidelines about writing for contemporary society:

  1. Timeliness: Producing good work, solid work, but the speed at which one produces should be quick. The news cycle in our contemporary society has become so fast. If a scholar does not address an important issue, they might be working at the margin of society, and that their ideas would never become relevant.
  2. Being relevant: Addressing issues that are relevant to different communities of audience is an important skill. Scholars often communicate with different audiences. Figuring out what issues are relevant to which community is an important first step.
  3. Framing the issue in a theoretical way: Attaching contemporary issues to bigger sociological debates is a trick that sociologists do in order to make sure that contemporary issues speak to timeless theoretical debates. This is a skill that graduate students like myself take a long time to learn. We’re still figuring out what the theoretical debates are. In order to relate a contemporary event to a theoretical debate, and write about it in an intelligent way, one needs to practice, and think a lot.
  4. Solid research: Before writing anything, one needs to gather evidence, and do solid research. Opinions without facts are useless.
  5. Jargon-free communications: Graduate students tend to synthesize other people’s ideas a lot to show that they are well-read, and that they understand dense social theory books. Yet in order to make a theoretical idea digestible to the mass public, one ought to know how to convey that idea without using sociological jargons. This is also a very difficult skill to learn. It takes patience and lots of practice to master.
  6. Feedback: As in any creative project, getting immediate feedback from trusted friends and colleagues is very important. Feedback is gold in the publication game.
  7. Develop a working relationship with journal editors: if one has a working relationship with editors, they would be more welcoming one’s next ideas, and next projects. Thus developing a solid working relationship with journal editors is very important. At the end of the day, academia is a reputation-centered economy. One has to develop one’s own reputation, and that one’s reputation is also judged by others. Reputation is currency in a knowledge economy.
  8. Submit and move on to the next piece: Having the next piece in the pipeline is very important. Once a piece of writing is submitted, the author should start another project immediately. This is to keep the momentum going. I cannot emphasize enough the importance of a publication cycle, and that the more one writes, the more one would be inspired to write more.

“Ideas beget ideas.” This idea never gets old. Whenever I get a publication out of the door, I feel happy about myself, and I feel inspired to write the next piece. Maybe one day, one of my pieces would become influential. Maybe one piece would become viral. Maybe my writings would change someone’s mind, and have some policy implications. As of now, those are far-fetched. My only writing goal now is to produce consistent work regularly. I prefer the productivity model at this point. At some point in the future, this productivity model might turn into a high-impact model. As I am still learning the ropes of publishing, the productivity model is most relevant.

Price of Living in a Poor Neighborhood

New York City is a strange place. The housing market is extremely tough for young families, and newcomers. Today I was curious to see how my neighborhood, Central Harlem, which is considered to be a poorer neighborhood than many other neighborhoods in the city. I googled to see the stats of the neighborhood with a specific emphasis on the housing market. Its median household income is $47,708 about two-thirds of the amount in New York, $67,844, and about two-thirds of the amount in United States: $61,937. In other words, I am living in a less wealthy neighborhood of the city. Its poverty ratio is 25.1%.the rate in New York: 13.6%, and nearly double the rate in United States: 13.1%.  My neighborhood is also poorer than New York City in general, and poorer than the United States.

However, when I look at housing value in my neighborhood. This is what I found:

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If a person owns a house at all, 50% of the houses have values of $671,000 or more. That’s a lot of money. It’s more than double the amount in New York, and more than double the amount in United States.

Here’s the further breakdown of the housing values in Central Harlem:

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I have always known that housing is expensive in New York, but when I look at housing values in my neighborhood, I was actually very surprised. 35% of owner-occupied housing units valued at 500,000 to 1 million US dollars. This is an exorbitant amount. 15% of the owner-occupied units are valued over 1 million US dollars. If I was to buy a housing unit (an apartment, or a house) in Harlem, and if I was a college professor at one of the local colleges with salary around 100K a year, given that I could save about 20% of my salary to buy a housing unit, it would take me at least 25 years to pay for a $500,000 apartment.

This calculation makes me realize two things. One, I do not think a college professor can buy a good house in Harlem. Maybe I have chosen a wrong career for financial stability. Two, if I want to remain in academia, I will join an exodus of New York emigrants to the suburb where housing is a lot more affordable than Manhattan. Manhattan squeezes out the middle class families.

At the end of the day, it’s such a contradictory existence. While my neighborhood is on paper poorer in terms of wealth, and income than other neighborhoods in New York City, its housing value is twice that of the city average. How are my neighbors getting by with  this precarious financial existence? What are some psychological and social impacts of both poverty on the lower end of the socio-economic spectrum, and housing pressure on the middle class, and upper end of the income ladder?

I have been living in this neighborhood for almost four years now. As a sociologist, I am immersing myself in the neighborhood experience, and getting to know “public characters” of the neighborhood in different aspects of life. The term public characters in Jane Jacobs’s definition are “often people like storekeepers, barkeepers, and pastors … By thinking, talking, and interacting out in the open, these people create our public life” (Eghbal). I am currently following the new public characters in the digital era in the New Harlem. My public characters are business owners, and tech founders. I would argue that in the new economy, business owners, and tech founders are creating a new kind of culture, and creating new kind of public life. This public life though is privatized, and operating around commerce.

I love this neighborhood, and feel that I have things to contribute. However, at this point, I am still not sure how I would be able to contribute to the enrichment of people from Harlem. So far, I have been struggling with the idea that I’m a gentrifier who is displacing somebody that I never got to know, and that I’m contributing to future waves of gentrification because with me, there are new restaurants and commercial places.

In a nutshell, living in Harlem is full of surprises on the cultural fronts, but on the economic fronts, the neighborhood is structurally difficult for everyone.

Principle Component Analysis

Today my goal was to figure out principle component analysis in R. This is something that I have been trying to understand for quite a while now. This takes some time to conceptual understand what PCA does. My RStudio is still arrested in an experiment. I wonder what kind of project I can use PCA for. Unlike the experiment I did yesterday with visualizing a text corpus in R, the experiment today is computationally expensive, and conceptually confusing. At the end of the day, I feel that I have not accomplished anything meaningful, and that my ability to use machine learning has not increased a single bit.

This summer I will be attending the ICPSR summer institute to study Machine Learning for Social Science Research. One of the lectures has to do with how social scientists have used PCA in their research. I need to ask the professor how I can use it in my own research. I need more examples in order to fully understand how it is used.

Figuring this particular machine learning module is both conceptually and technically challenging at this point. I wonder what kind of dataset should I use in order for this particular technique to be useful.

Sometimes, it takes a well-designed exercise for me to fully grasp what the particular technique does, and how I can use it in my future work.

WHAT DOES IT ALL MEAN I SO CONFUSE - Jackie Chan Meme - quickmeme

Visualizing Data as Discovery

I have been obsessed with data visualization lately. My go-to tool at this point is till R, which I have been told over and over again that it’s not as versatile as Python. However, it’s the matter of path dependence, and that I am used to figuring out how to to ask the right questions in R in order to get desirable results.

With Python, different steps that I need to figure out to get desirable results are still black boxes to me. While writing this blog post, I have realized that I really need to master the Python programming language this summer. I have gotten down the basics. It is the matter of practice. Thus, this is the right time for me to actually sit down, and become really familiar with python, and be able to produce work using python programing language.

Back to the issue of data visualization. Today, I spent 8 hours straight trying to figure out how to create stacked chart in R. I have been trying to create it for quite a while. It started about 4 weeks ago when I promised my research partner that I would create a stacked chart figure for our text mining paper. I asked all people I know around to help me. They all did not deliver. Today, it turned out, I rolled up my sleeves, sat down in front of my laptop, and figured how to create the chart. My final result is not as clean as what I would have liked. It’s nowhere close to a scientific journal level quality. But the figure conveys the main idea, and that it is sufficient for me to draw some conclusions from the data.

This is the figure that I produced after a day trying to create it. Besides, it also took some serious conceptual understanding of what this figure actually represents. In other words, I learned both the technical skills, and the conceptual understanding behind the process of creating it. legend18

What I did was that I downloaded a corpus of text from the subreddit podcasting, a community dedicated to creating podcasts. My goal was to create a stacked chart that demonstrates different topics over time. The topics are represented by trigrams. Specifically, I calculated top trigrams per month, and charted them over time. Even though I downloaded all content from the subreddit, which started in 2010, I found that trigram chart only matters once I narrowed down the date range to 2016-2020.

The resulting figure shows that the subreddit started with accepting promotional podcasts, then became dominated with weekly podcast discussions, and technical discussions (such as mic, mixer audio interface). One topic that remains central over time is the different podcast distribution platforms (Apple Podcast, Google, Spotify).

The overall topics concern with technical aspects of producing content, and the different main platforms that one could distribute episodes, as well as finding shows. From these various topics one can conclude that in the past 5 years of the previous decade, the podcasting community focused a lot on the technological aspects of the field.  Technology matters from both sides: creation and consumption. Thus, it seems that the main driver of the podcasting field so far has been the sheer development in technology both for content creation and content consumption. What is surprising to me through this exercise is that the discussion about how to monetize a podcast doesn’t show up at all  in the top trigrams per  month analysis. This raises a question about whether the goal of being able to make money from producing a podcast ever a goal for a podcaster.

After spending my weekend working on this little project, I actually felt good about my product. I felt that I actually spent a day building something, and that at the end of the day, I actually saw the result of what I built. This satisfying feeling made me recognize how much I actually appreciate coding. One computer scientist I followed wrote in his newsletter that code doesn’t lie. One knows the exact effects of all the actions. When the final results are not attained, no way bullshitting would help.

More visualizations will come out of my work in the next weeks to come. So far, I am very happy with my progress in learning data visualizations. The more I get into visualizing data, the more I understand the importance of being able to use charts and graphs to understand the social world that we’re living in.

Students’ Reflections

When students submitted their final exams, some sent me notes saying that they had a productive semester together with me despite bumps and also Covid19!. Following are a few that I exceptionally appreciate

“Your class was one of the more useful ones I’ve taken in my master’s program.”

“Thank you so much prof for all your patience, communication and feedback really made this semester very smoothly.”

These feedback really made my heart smile! Teaching has gradually become more enjoyable to me because I can now motivate students my students to give more to the class, and to their final projects.

Community Gardens in NYC

This week, I attended a presentation about community gardens in New York City. From a sociological point of view, it turns out that community gardens can be considered an extremely interesting social phenomena. For example, community gardens could be points of ethnic and racial conflicts (see research by Sofya Aptekar). During the talk, I figured out that there are two community gardens on my block. This is wild. I have walked by them many times, and have seen people hanging out in them. But I have never walked in the gardens, or started planting any trees. And my digging into the community garden data available on NYC OpenData reveals extremely interesting patterns.
6clusters
The dataset provides 536 data points for data analysis. This is indeed an incomplete dataset because I learned that there should be about 600 community gardens in New York City.
Then I did a k-means clustering analysis to create different clusters. I simply went on Github  and got some off-the-shelf python code that do spatial clustering.  Then I altered the code such that it works with my computer, and my data. After trying 3, 4,5 and 6 models, I concluded that 6 clusters look like a reasonable model for this dataset. The above figure is the final result of the cluster analysis. One can do more fancy GIS visualizations. I think that this figure is already very telling about spatial clustering of community gardens in New York City.
The common wisdom is that community gardens are located in the low-land value areas.  This figure certainly supports the sentiment, but it also shows a more complicated picture. The dense clustering areas are black dots or those community gardens in the Bronx. Then there is a dense area in between Brooklyn and Queens. The rests are pretty sparse. Looking at the map, one sees that Upper Manhattan is grouped with the Bronx (black dots), some parts of Queens, Brooklyn, and lower Manhattan, and the Upper West Side are grouped together. Then the middle part of Queens is its own cluster. And outer part of Queens is another cluster. Staten Island is another world in and of it self.
I showed this map immediately to a colleague and she confirmed that the map captures what the literature says. The literature says that community gardens are mostly located in low land-value areas, relatively low land values, with ethnic and racial minority populations, and all on city-owned land that the city took control of because the building owner did not pay property taxes for three years.
So that’s my attempt at getting a handle of k-means clustering. I’ll be working more on k-means clustering for other projects. The more I use this technique, the more I think that there are lot of ways that I can use it in different projects. Over the summer, I’ll improve my python skills to write my own k-means clustering code. As of now, I am happy learning and working with other people’s codes.

The Professor’s Daughter

I finally got around to finish the novel, The Professor’s Daughter by Emily Raboteau. I was hooked from the very first page. However, it took me about two months to finish reading it because of the Covid-19 pandemic. The healthcare crisis took away my attention to concentrate on anything other than the virus itself. Now when a new normal has been established, I could go back to my reading-novels routine.

The novel explores black/white identity through the lens  of a mixed race female protagonist. She is a daughter of a famous African American professor at Princeton, and a white Catholic mother. Her brother died early when she was in college, and her father left her mother for an African American graduate student. All the identity questions are examined through complicated, entangled relationships within her family, and to an extent her extended family, then friends, and lovers when she’s grown up.

The writing is extremely approachable. The book started out when Emma, the main character, was a child. It follows her journey into teenage years, and then to early adulthood. It reads like a memoir. Maybe it’s partly a memoir by Emily Raboteau, whose father is indeed a very prominent figure in African American studies at Princeton. Yet, I could also feel that the story is constructed. It’s another world.

The book is so relatable. It’s the growing up story of a person who is struggling to come to terms with her identity. Being an acute observer, the main character reveals a world of inequality, of cultural clashes, and of minority struggles. I can relate to the main character’s experiences on many levels. On one level, as an introverted child myself, I observed the adult world around me, and could not make sense of it, until one day I decided that I was more of an adult than the adults who were supposed to raise me. On another level, the book revealed the other side of academia, the side of the providers of education. Emma’s story is a story of growing up in the shadow of a famous academic, who is so smart that people around him are afraid of him, or not being able to relate to him at least on the intellectual aspect of life. That’s the struggle of many academics. I can hardly discuss what I do to my parents because neither would they understand nor are they interested. So I stopped my communications with them. My obsession with some small details about the world of online extremism is none of my parents’ interests. Probably they would ask me why I study a phenomenon so endemic to a Western society to start with. Such question is legit, but it also does not explain why I would be so obsessed with figuring out an answer to explain why such a phenomenon happens in a place and time that it happens.

I started this reading project back in February, my female novelists month. The moment I put down the book The Tiger’s Wife, by Téa Obreht I started this current project. Weirdly, how I call reading a novel a reading project? My mind seems to think of everything I do in life now as a project: cooking project, baking project, composting project, writing project, etc. My life is compartmentalized into different projects. They are all running in parallel at the same time. They have different processes, and different end points.

Reading one book after another, I could not help but compare the two writers’ writing styles, narratives, and pacing. Both utilize very fast pacing. Both are very intelligent. Both are very interesting. However, The Tiger’s Wife has a more exotic feeling to it. It transported me from New York City to a far away place in the former Yugoslavia, while The Professor’s Daughter transported me to a familiar place of Princeton. Both books are narrated from female protagonists’ points of view. They are sensitive to women’s experiences. They are full of energy, and I feel like I am apart of the story.

Now getting back to my new normal, I am hoping that I could use this quarantine time to read more books, more novels, and more interesting narratives. Maybe I should also write a few short stories myself being sheltered in place.

Book Review: Minor Feelings by Cathy Park Hong

Since I was racially assaulted in public a few weeks ago, I have been thinking a lot more about the rising anti-Asian sentiment in America resulting from Covid-19. Being stuck at home with a laptop, I read more about different ways racism against people of Asian descent manifests, and how the victims deal with this new social reality. One author who popped up quite a lot in my search was Cathy Park Hong. I read a few op-ed pieces she wrote, and they all referenced her recent book Minor Feelings, which explores the question of identity as an Asian American, specifically Korean American, born, and raised in America.

Hong defines minor feelings as :

the radicalized range of emotions that are negative, dysphoric, and therefore untelegenic, built from the sediments of everyday racial experience and the irritant of having one’s perception of reality constantly questioned or dismissed. Minor feelings arise, for instance, upon hearing a slight, knowing it’s racial, and being told, Oh, that’s all in your head … [M]inor feelings are “non-cathartic states of emotion” with “a remarkable capacity for duration.”

These feelings are emotions that an individual experiences pertaining to their racial existence. They sometimes make the individual doubt themselves whether their interlocutor was being “racist or racial” toward them. These were experiences that the majority around them do not feel, and the racial minority person does not have the language to describe. Thus these feelings remain “minor,” sometimes inconvenient, sometimes frustrated.

These feelings are so specific to American society that they “occur when American optimism is enforced upon you, which contradicts your own racialized reality, thereby creating a static of cognitive dissonance.” America is a place full of contradictions. On the one hand,  it is a neoliberal land, proud that it offers every one opportunity. On the other hand, it’s an old capitalist society that thrives on the back of people of color since the onset. Depending on what part of America, an individual wants to see, they would see different parts.

Then Hong goes on relating these feelings to her own experience growing up in America as a minority person: “To grow up Asian in America is to witness the humiliation of authority figures like your parents and to learn not to depend on them: they cannot protect you.” Second generation often has to defend their parents. They are forced to grow up, and deal with the cruel society, which takes no excuse when humiliating your parents, and everything you think should be respected. You take their pains, and humiliations as your own because at the end of the day you see yourself in them.

The word “minor” is aptly used in this book to describe the fact that Asian Americans’ uncomfortable feelings about their existence in America. Their feelings are so “minor,” so minuscule that the mainstream society does not care. No-one would take their silent sufferings seriously:

The indignity of being Asian in this country has been underreported. We have been cowed by the lie that we have it good. We keep our hands down and work hard, believing that our diligence will reward us with our dignity, but our diligence will only make us disappear. By not speaking up, we perpetuate the myth that our shame is caused by our repressive culture and the country we fled, whereas America has given us nothing but opportunity… Racial trauma is not a competitive sport. The problem is not that my childhood was exceptionally traumatic but it was in fact rather typical.

Asian Americans are quiet, keeping their heads down, and their hands work. Asian Americans are so quiet that they become invisible. But being ignored, and being condescended to are daily experiences that they lost any belief in themselves, and their abilities.

Shame is an integral part of the minor feelings. It works insidiously to keep the victims’ heads low, and their mouths shut.

My parents are those who survivor instincts align with this country’s neoliberal ethos, which is to get ahead at the expense of anyone else while burying the shame that binds us. To varying degrees, all Asians who have grown up in the United States know intimately the shame I have described; have felt it oily flame … Shame is an inward, intolerable feeling but it can lead to productive outcomes because of the self-scrutiny shame requires.

Shame is a feeling that binds us. If you fail, your parents feel shameful for you. If you fail, your community feels shameful for you. Shame is both an individual, and a collective experience.

After the racial assault incidence, I felt more solidarity with the Asian community in this country.  Reading Hong’s book made me realize the indignity that has troubled them for decades even centuries. The concept “panethnicity” explains this feeling that I have with other ethnic groups.  I used to embrace the bright, positive, optimistic part of American society, and ignore the dark history of American racism. Covid-19 whips racist residues to the surface.

I find comfort in reading Hong’s book. It’s deeply personal, but also deeply structural. It’s a memoir not of herself, but of many Asian American artists who are trying to come to terms with the racist society that they were born into and raised. The book both liberates and troubles me. It frees me by giving me vocabulary to describe my intimate ontological feelings. It troubles me by revealing the ugly face of American society that I refused to see for a long time.

This book is also very refreshing from the point of view of race/ethnicity studies. It was written as an autobiographical exploration by a poet. Her references are very different from what I would use for my regular scholastic exploration. Normally, whenever I want to understand Asian American experiences in American society, I would go to sociology giants in my field such as  Dina Okamoto or Jennifer Lee. Hong instead cites literary giants that she admires. I see her professional inspiration, and aspiration in the book. By reading the book, I was  introduced to a world of intellectuals who study race/ethnicity issues from a very different perspective from mine. Many a times, I can feel that she is talking about a concept that I might know how to express in sociological terms. However, she talks in a way that is more relatable, more lyrical, and also more humanistic.

Sometimes she speaks for me: “At the time, I couldn’t relate to some of the Asian American fiction and poetry I came across. It seemed, for the lack of a better word, inauthentic, as if it were staged by white actors. I thought maybe English was the problem. It was certainly a problem for me.” I feel unheard many times. When I look inside into the world of books, my experience is also not recorded anywhere. My quest for self understanding both in the real world, and in the fictional world yields no fruit. Maybe I am just waiting for that book to be written. Or maybe someday I will write a book myself.

The book shows me that I am not alone in resisting to write about my own racial experience: “I still clung to a prejudice that writing about my racial identity was minor and non-urgent, a defense that I had to pry open to see what throbbed beneath it. This was harder than I thought, like butterflying my brain out onto a dissection table to tweeze out the nerves that are my inhibitions.” This precise feeling that exploring one’s own racial and ethnic identity is “minor,” as not “important” leads to the fact that there are not many materials for me to use to understand my experience.

Many a times, I feel my story has not been told. I feel my history is incomplete. I used to think that Americans did not understand me. Then I went to graduate school, and started to hang out with historians of Vietnam. I learned that archives of the Vietnam war just opened up. At least more will be told about the Vietnam War, but as of now, the history remains incomplete. But my experience, my people’s experience are not only about the Vietnam War.

For a person with an incomplete history, sometimes I become incomplete myself. I am confused in American society, because I do not fit the mold of the Vietnamese refugees or their second generation. People’s preconceived notions me fall apart when we talk. That’s the minor feeling that I am experiencing in American society.

Unless we are read as Muslim or trans, Asian Americans are fortunate not to live under hard surveillance, but we live under a softer panopticon, so subtle that it’s internalized, in that we monitor ourselves, which characterizes our conditional existence. Even if we’ve been here for four generations, our status here remains conditional; belonging is always promised and just out of reach so that we behave, whether it’s the insatiable acquisition of material belongings or belonging as a peace of mind where we are absorbed into mainstream society. If the Asian American consciousness must be emancipated, we must free ourselves of or conditional existence.

Even in the writings of Viet Thanh Nguyen, I do not find myself. His writings are sensitive to Vietnameseness, but not femaleness in me. His writings are sensitive to the sufferings of the Vietnamese refugees, but not those who grew up in post-Vietnam War  impoverished North Vietnam like my parents. His writings were about downward social mobility, when a middle-class Vietnamese family in South Vietnam became working class in America without any belonging, and their social networks. How about my family living in the north of Vietnam suffering impoverishment, and Cultural Revolution-style poliies, and pulling their own bootstrap to survive through “Thoi Ky Bao Cap” or The Subsidized Era? These stories are not told, and I could not find myself in the pages. I could sympathize with people’s sufferings, but my Vietnameseness is different from those that I have read in the pages in America, and from the mainstream American’s imagination of what a Vietnamese person should be.

In this sense, my uncomfortability, my frustration, and my invisible existence resemble what Hong calls “minor feelings.” They are inconvenient, but not world-shattering to the majority population, or even in my case my co-ethnics in the United States.

Teaching How to Code Online and in Person

I just finished the carpentries instructor training, which allows a potential instructor to join the Carpentries community. What does the Carpentries community do? one might ask. The Carpentries “teach foundational coding and data science skills to researchers worldwide.” Their data science teaching workshops operate mostly through enthusiastic certified volunteer instructors.

I still need to complete two more steps in the “checkout” requirements, including doing a 5-minute teaching demo, and attending a teachers’ guided discussion online in order to be certified as an instructor.

How did I hear about the Carpentries? A mentor at Hunter College attended the training last summer, and mentioned it in passing last summer. The name piqued my interest. I went online, learned more about the program, and filled an application to attend an instructor’s training. It took about seven months since I applied until I heard back that I could attend an instructor’s training workshop either online or in person.

Because of the lockdown, many of my regular activities have been canceled, or postponed. I found that this is the right time to get the certificate. So I registered for a  two-day online workshop.

My experience? Very positive. I learned a lot about coding, and how to teach people to code both online and offline. I spent two days to learn how to teach coding with more than twenty people from around the country. Participants came from diverse backgrounds. They were professors, librarians, PhD students, post-docs, and educators. I found that I benefited from learning from their diverse experiences. Specifically, during many breakout sessions, I had a chance to learn from a statistics professor, a post-doc in neuroscience, a few computational linguists, a geographer, and a couple of librarians. This group of professionals really made my being at home more interesting.

Learning about Teaching: The workshop made me consciously think about building blocks of teaching another person a set of skills. The workshop provided a mix of education, psychology concepts for instructors to understand how people absorb information, and learn new skills. It was empowering to learn about what makes students learn well, and what prevents them from learning.

Learning about Participatory/ Live Coding: At this point, I am still conflicted about participatory coding pedagogy. What it means is that instructors demonstrate live coding in front of a group of participants. On the one hand, it helps learners participate in the thought process, and engage with the instructor’s programming process. On the other hand, it feels pretty taxing on the part of the instructor. There are many variables that the instructor has to control for. Unlike having a code that is already written in advance, the instructor has to improvise on the fly at times. I find this to be cognitively demanding, unless the instructor is very experienced at talking about technical steps.

I want to know why this is a good pedagogy for teaching beginners to code. In my experience, doing live coding with students often distracts students from the fundamental statistical concepts that I want to convey to them during the class. In my Data Mining class, I used to do live coding. But then I realized that I had to compromise on the materials that I wanted to teach them. The entire time, my focus was on whether my students were able to type correctly a line of code, or whether there was any execution issue in the process. It was not effective in the sense that many of those issues might have nothing to do with the class materials. Thus I decided early on in the class that live coding was not helpful for the purpose of my class. Instead, I provided students with the Rscript in advance, and they could use it to run while I was giving them a lecture on random forests, or support vector machine.

Now reflecting on the instructor training workshop that I just attended, and my own experience in teaching people to code, and use the R programming language, I realized a few things. One, live coding is helpful for beginners. In other words, it would be beneficial if I organized workshops to teach my students concepts at the beginning of the class. Maybe I could use one or two lab sessions to demonstrate how to use various lines of code. Then in the second and third parts of the course, I could provide already written scripts to demonstrate statistical techniques, concepts.

In other words, the instructor training workshop highlighted the different emphases that one would want to teach. The experience was indeed refreshing because I was challenged to ask questions about my own personal practices, and what would be considered as ideal in teaching novice learners how to use programming languages.

The workshop also piqued my interest in conducting a workshop to show people how they could use different programming languages to achieve their research goals. Once I get certified as an instructor, I would love to contribute to the carpentries community by offering my own workshops on text analysis in R or in python.

 

Cultural Intermediaries in an Infoglut Era

I am constantly looking for new things to read, not so much for things to watch. Every month, there are many new movies and TV series that are added to Netflix and Amazon Prime. I don’t really get excited that new movies are added to the database and are available for my consumption. What gets me really excited is news that some original novels that receive great approval from the reading public.

Most recently, I read The Tiger’s Wife by Téa Obreht. The novel has non-linear narrative, and being told from two different points of view: a grandfather who lived in the past, and a granddaughter who lives in the contemporary world. The idea of having a tiger moving about in a snow-covered area somewhere in the former USSR triggered my deep imagination.  Many elements in the novel work for me: the narrators, the scenery, and the language. It’s fast-pace, mesmerizing, and full of surprises.

I constantly seek recommendations for novels and non-fiction readings from my friends.  Other times, I rely on the crowd wisdom of the internet. Most reliably, go back to the New York Review of Books (NYRB). In many ways, I  trust NYRB more than the other channels. I trust its institutional reputation, and the workforce that powers the content that the institution publishes. NYRB has introduced me to many books that I would never have discovered otherwise. This week, I received an email from new York Review of book about a new comic:

 

Screen Shot 2020-04-15 at 12.18.19 PM

This is such a refreshing email during this strange time. The email introduced readers to a French comic graphic novelist, Blutch. I never heard this name before, but the illustration is very tempting. There’s not much information in English about him. Wikipedia article about him has only French and German versions. I can barely read French, but German is not a problem.  The author looks like an interesting figure in the contemporary French comic scene. Besides, I had no idea about French comic books. This email introduced me to something that I never knew before, but would love to get some information on.

I went to the internet, and found his comic books in French. My French level is not that high, but the illustrations just look really cool. They re-sparked my interest in French. I feel like by simply skimming these pages, I could acquire some new French vocabulary.

The process of discovery was just so much fun. I got lost in the weeds of information for hours.

This experience reminded me of an important concept in sociology of culture: “cultural intermediaries.” They refer to occupations and workers who engage in the process of production and circulation of symbolic goods and services.

In the specific experience of getting books to read, I rely on three sources: individuals/ personalities I know, reputable institutions, and the internet. By relying on individuals  whom I know, I rely on my social network. The fundamental idea behind this mechanism is homophile. It works as follows: if I am friended with people whose interests are similar to mine, whatever interests them, and whatever they have approved to be good, and interesting, there would be high probability that I would enjoy what they enjoy. Thus I could save time by vetting the books.

Institutional cultural intermediaries are institutions like NYRB. I do not know employees of the institution personally, but I have had prior experiences relying on the institution, and these experiences have proven to be reliable. The institution’s reputation is what I rely on mostly. The idea is that if many people have relied on the institution, and that they had successfully use the information provided by the institution, then I could also rely on the institution. There is a temporal aspect in evaluating an institution’s reputation. The institution has existed long before I was born, and possibly will remain when I die.

Finally the internet is a melting pot of both good and bad recommendations. Sometimes I could rely on Amazon’s reviews. Other times, they prove completely a waste of time. Many databases, and websites use recommender systems to recommend books to users. However, other than Netflix, I find these different recommender systems to be not yet useful, or that they are not yet tailored to my interests. There is a social dimension in taste, and cultural transmission that algorithms seem to not have figured out. In other words, algorithmic or probabilistic models are not sufficient in capturing nuanced human cultural consumption and changing tastes. Thus, I leave algorithmic cultural intermediaries outside of my analysis for now.

It’s worth noticing the differences between the first two mechanisms.

First in terms of similarities. Trust is the big factor in both scenarios. In the first scenario, it’s the intimate trust. And the second scenario, it is public and social trust in institutions.

The first mechanism relies on my dyadic relationship between me and my friends in my social networks. There’s a high level of intimacy. But it’s also small in scale.  I could quickly evaluate whether I should trust a friend or not, and by extension their tastes in certain things. This mechanism cannot be scaled up. It relies solely on my small social network, and whom I know.

In the second mechanism, I have less power to control what the institution does, and whether it suits my interest. The institution is often a multi-purpose institution, and it sometimes or most of the times do things that I have no interest in. For example NYRB does not always recommend things that I would enjoy. But in general, I respect what the institution recommends. I think that the books and the reviews that they publish are of high quality. They might not suit my interest, but if they do, they are very spectacular. I have to take a leap of faith that the institution does what it is supposed to do based on its social reputation. Over the course of almost four years, I have benefited from NYRB’s main core business: creating content about books.

To this end,  I think a few lessons learned here is that cultural consumption still relies mostly on cultural intermediaries through social network, and social institutions. In the Web 2.0 age, and the rise of new cultural intermediaries such as recommender systems, and mass reviews on Amazon, and other websites, I would want to know which channel influences consumers’ consumption behaviors the most. Furthermore, is there any new cultural intermediaries occupations that  were born out of the Web 2.0 era, or that algorithmic recommender systems would also automate all of these occupations through probabilistic modeling, or that new occupations would be created because of the new spaces that algorithms create.

 

 

 

Laundry, Modern Life and Hand Work

I have definitely become more OCD with the lockdown.

As capitalism has come to a halt, my once regular daily activities such as going to work, performing research tasks, and reporting to my advisor, boss, research partners stopped. Now being stuck in a tiny apartment in New York City, I am trying to fill in the time with activities that make my mind and my physical body active.

I have always thought that I would never become a housewife, a title I detested. Now, I am stuck at home. What I have been driven to is no longer my library with hundreds of books in many different languages. What I actually find comforting is cleaning the house, washing clothes by hand, and keeping my kitchen spotless. Now I enjoy reproductive activities such as sewing DIY face masks, taking care of house plants, and most interestingly spending fifteen minutes a day to hand-wash clothes.

This new-found enjoyment challenged my prior assumption that reproductive activities were not as enjoyable as productive activities. Reproductive activities could be very therapeutic.

More importantly, it is the question of hand-work vs. intellectual work. My life before Coronavirus (BC) was very intense in terms of cognitive work. When coronavirus pandemic hit, I was reaching the point of cognitive overload. During the first few weeks of Covid-19, I expected that the situation would soon be over. So I had no change in my behaviors toward intellectual work. Now the American and the world economies seem to be both going toward recession. Productive activities are slowing down. I feel that I can take my time, and not focusing too much on my productive activities. This is when hand-work comes in. I am cleaning, and disinfecting my apartment at least 3 times per day. I wash piles of dishes twice a day. Then, I wash clothes by hands also twice a day. These were activities that I did only intermittently before coronavirus pandemic. At least one thing I see as silver lining during this period of time is that I have become more OCD, and paying more attention to cleanliness of my living environment.

On Hobby and Meaning of Life

“Why don’t you have a hobby?,” asked my roommate recently. I thought I had one such as writing this blog. It turned out blogging about my lived experience, and applying sociological theory on myself is technically not a hobby. Ultimately the question whether blog writing constitutes a hobby depends on the question of intent. It is an activity that I enjoy immensely because I derive meaning out of writing things about my life, my studies, and my research. Yet it is still a work-related activity. My intention from the outset was  to improve my writing, and my understanding of sociological theories. All taken together writing this blog is more work-related than most of my other time-consuming activities that I have engage in. Writing this blog entails doing research about a subject matter, understanding it, summarizing it, and giving some opinion about it in a succinct and intelligent manner.  When taking the process apart, there are a lot of cognitive steps that involve. Yet, by this point writing a blog post has more or less become second nature. As soon as I have an idea, I can muse on it, and write a blog post to express my thinking and feeling about a subject. So a potentially work-related activity could gradually become a pastime, leisure activity once one figures out the formula, and make it easy, effortless, and enjoyable.

Now back to the idea of my not having a hobby. The above comment at first hurt my feelings because it suggests that my life is incomplete or that I am too career-focused, or that I never ask a deeper question about the meaning of life, or how to live life to the fullest. Then I took a step back and ask a few questions why it is the case.

What is a hobby? 

It became clear that I was confused about what defines a hobby, and what it does to me. Wikipedia defines it as follows:

hobby is a regular activity done for enjoyment, typically during one’s leisure time, not professionally and not for pay.

This definition captures the idea that hobby is what one does during one’s leisure time, the purpose of which is not for pay. From a sociological point of view, a hobby is what one does outside of the productive realm. It pertains to the reproductive realm in human activities.

Sociologists of leisure study hobbyists, and hobby activities such as chess playing, tour guide, quilting, etc. They basically study how we create meaning through hobbies, and how do hobbies then reshape us in the social world. They notice that the distinction between a hobby and a paid activity is blurred in many situations.

The relation between work and leisure can also be unclear: research indicates that some individuals find skills that they have acquired at work useful to their hobbies (and vice versa), and some individuals have used leisure activities to advance their work careers. (Wikipedia)

This is particularly true for people who work in entertainment industries. For example, when I interview podcasters, some professional podcasters say that they enjoy doing it so much as hobbyist podcasters, so they quit their former job to become professional podcasters. Some hobbyist podcasters have been able to negotiate with their employers to create new positions, or to negotiate a raise. Musicians  also enjoy playing music as a hobby.

Why do I not engage in a hobby? 

Personally I do not have a hobby that I regularly devote time to. I never thought about the question. I dabbled in playing guitar for a while. Then I also tried the ukulele. None of these instruments panned out. There were three main reasons non of those musical activities stuck: (1) having no time for myself outside of work, (2) no childhood experience in having a hobby, and (3) no reinforcement mechanism.

First, I have not had enough time to follow anything through, and moved beyond the beginner’s level. Most of my time has been spent on studying sociology, improving my writing, trying to finish my dissertation, and leaving graduate school. Graduate school life is so overwhelming that I have totally given in, and not questioning why I have not carved out  time for my own personal enjoyment. This is partly my fault of not drawing a clear line between graduate school, personal life, and having a clear definition of what makes life meaningful to me as a graduate student, and in general a person. I was very busy trying to learn the tropes of becoming a professional sociologist. This identity-formation process has taken over, and I have forgotten that besides being and becoming a sociologist, I am also a full person with life history, and personal interests. Becoming a sociologist does not erase these multiple facets of life. Becoming a sociologist simply means that I have accumulated a different way of seeing, understanding, and analyzing the word that is specific to the profession of sociology.

Whenever I do not spend time studying, doing research, or writing papers, I would teach, or do administrative work that would take another huge chunk of time. After my work day, I often feel extremely exhausted. Time compression was what I feel on a daily basis. I feel that I am constantly on the move. There is constantly something that occupies my mind. There would be no space available on my calendar for a recreational activity such as playing music. I have been totally overwhelmed by work.

Now suddenly because of Covid-19, a lot of my work-related activities have been canceled. A big chunk of time  has been freed up. And I start thinking about how I can use my time in a meaningful way. The question of having a meaningful but yet not work-related activity came to the fore, while I realized that prior to the Covid-19 Pandemic, my life was so consumed by work.

Second, possibly having a hobby was not something that I was raised to think that it would be an important part of life. Did I have a hobby when I was a teenager? The answer is no. I could not recall if I did anything for fun in high school. Most of my fun activities involve some academic activities such as learning English on my own, or I would spend much of my free time playing video games, or watching Korean dramas. Did I create anything with my hands such as crocheting, or knitting. I did a bit of those, but I never stuck to one activity for a long time. Most of what I did was solitary. Possibly, I downplayed the importance of these activities by saying that they would not contribute to my academic advancements. I think I still have this attitude.

Third, I have had no reinforcement mechanism, which could mean having a regular schedule to practice guitar, or to be a part of a community of hobbyists. Being a part of a community of practice is very important. One could practice ukulele for a long time, but if one does not use the skills, it would be stale at some point. I feel that this is the social aspect of having a hobby that makes life even more meaningful.

In short, I have downplayed the benefits of having a meaningful hobby, overwhelmed myself with work-related activities, and not being a part of a community of practice. Now I want to ask a more philosophical question about why and how a hobby would make life more meaningful, and fulfilling especially for our contemporary life.

Why should one have a hobby? What is the problem of having no hobby? Is it the problem of contemporary life? 

Looking at my experience, I realized that it is not unique. It is very representative for a lot of people living in a capitalist/modern society which values productive activities by giving a money tag to each activity. Even if one engages in a hobby activity, there is also the question of monetization, that is how one can make it a money-generated activity. Living in such a society, one would unconsciously prioritize productive activities, while giving little attention to recreational activities that bring joy, fulfillment, and happiness to one’s life.

My experiences growing up as a teenager in Vietnam have been a story of social mobility, and then surviving in another society. Now Covid19 Pandemic suddenly provides me with an opportunity to reassess on what has been my priority, and the emotional cost that social mobility meant to my well being.

On a societal level, the crisis presented an opportunity for serious structural changes. I can feel that these changes are coming in the economic, political, and cultural realms. On the personal level, the crisis presented me with an opportunity to reflect on what is the priority of my life, and ask the question what makes life meaningful, and worth living.

A healthy hobby is essentially a part of the question “what does it mean to live a good life?” I asked this question to my close friend last week. In our exchange, I recognized that I have read the answers to this question many times. But most of the time, I encountered writings by men, whose answers based on their lived experiences. My original thought was that the question was fundamentally gendered. However, my friend reminded me that the question by nature is not gendered. The answers could be gendered because it is important to ask who gets to ask the question. The person who could ask such question is in the privilege position to have time to contemplate on a philosophical journey. The one who comes up with the answer, and provides answers to that question is also in a privilege position  because they actually have time to pursue a hobby or some activity that is meaningful while the majority of the population are still striving to survive.

To this end, I think that the question why I do not have a hobby has answers rooted in both the personal, and the societal. On the one hand, I have been neglecting the emotional aspects of my well-being. On the other hand, I live in a society that downplays non-monetary benefits of leisure activities. Going forward, I am determined to correct this empirical imbalance by introducing a regular activity that makes me happy, and reducing the amount of work-related activities to live a meaningful and fulfilling life.