Archive for the ‘fabio’ Category
This is the last post for now about The Triumphs of Experience. In today’s post, I’d like to focus on one of the book’s major findings: the extreme damage done by alcoholism. In the study, the researchers asked respondents to describe their drinking. Using the DSM criteria and respondents’ answers, people were classified as occasional social drinkers, alcoholics and former alcoholics. Abstainers were very few so they receive no attention in the book. People were classified as alcoholics if they indicated that alcohol drinking interrupted their lives in any significant way.
The big finding is that alcoholism is correlated with nearly every negative outcome in the life course: divorce, early death, bad relationships with people, and so forth. I was so taken aback by the relentless destruction that I named alcoholism the “nuclear bomb” of the life course. It destroys nearly everything and even former alcoholics suffered long term effects. The exception is employment. A colleague noted that drinking is socially ordered to occur at night, so that may be a reason people can be “functioning” alcoholics during the day.
The book also deserves praise for adding more evidence to the longstanding debate over the causes of alcoholism. This is possible because the Grant Study has very rare, and detailed, longitudinal data. They are able to test the hypotheses that development of alcoholism is correlated with addictive personality (“oral” personality in older jargon), depression, and sociopathy. The data does not support these hypotheses.By itself, this is an important contribution.
The two factors that do correlate with alcoholism are having an alcoholic family member and the culture of drinking in the family. The first is probably a marker of a genetic predisposition. The second is about education – people may not understand how to moderate if they come from families that hide alcohol or abuse it. In other words, the family that lets kids have a little alcohol here and there are probably doing them a favor by teaching moderation.
Finally, the book is to be commended for documenting the ubiquity of alcoholism. In their sample, alcoholism occurs in about 25% of the sample of men at age 20. By the mid 40s, alcoholism reaches a peak, with about half of men being classified as alcoholics. After age 50, it then declines – mainly due to death and becoming a “former alcoholic.” If there is any generalizability at all to these findings, it shows that alcoholism has probably been wrecking the lives of millions and millions of people, somewhere between a quarter and half the population. That’s a profound, and shocking, finding.
A while back, I discussed a new technique for organizing and displaying information collected through qualitative methods like interviews and ethnography. The idea is simple: the rows are cases and the columns are themes. Then, you shade the matrix with color. More intense colors indicate that the case really matches the themes. Clustering of colors indicate clusters of similar cases.
Dan Dohan, who imported this technique in from the biomedical sciences, has a new article with Corey Abramson out that describes this process in detail. From Beyond Text: Using Arrays to Represent and Analyze Ethnographic Data in Sociological Methodology:
Recent methodological debates in sociology have focused on how data and analyses might be made more open and accessible, how the process of theorizing and knowledge production might be made more explicit, and how developing means of visualization can help address these issues. In ethnography, where scholars from various traditions do not necessarily share basic epistemological assumptions about the research enterprise with either their quantitative colleagues or one another, these issues are particularly complex. Nevertheless, ethnographers working within the field of sociology face a set of common pragmatic challenges related to managing, analyzing, and presenting the rich context-dependent data generated during fieldwork. Inspired by both ongoing discussions about how sociological research might be made more transparent, as well as innovations in other data-centered fields, the authors developed an interactive visual approach that provides tools for addressing these shared pragmatic challenges. They label the approach “ethnoarray” analysis. This article introduces this approach and explains how it can help scholars address widely shared logistical and technical complexities, while remaining sensitive to both ethnography’s epistemic diversity and its practitioners shared commitment to depth, context, and interpretation. The authors use data from an ethnographic study of serious illness to construct a model of an ethnoarray and explain how such an array might be linked to data repositories to facilitate new forms of analysis, interpretation, and sharing within scholarly and lay communities. They conclude by discussing some potential implications of the ethnoarray and related approaches for the scope, practice, and forms of ethnography.
Today, we’ll continue discussing George Vaillant’s The Triumphs of Experience, the 70 year long life course study. One of the major findings of the study is the importance of early childhood family conditions. The initial phases of the study asked participants to describe their childhood environment. Were their parents open and warm? Cold and removed? Divorced or still married? Also, the Grant study investigators had the opportunity to interview parents and other family members on occasions. Did the interviewer think the mother was involved or removed?
Using these data, the Grant Study investigators coded a number of variables reflecting family environment. The recorded stratification variables (employed v. unemployed, working class v. upper class), structure (divorced v. married) and emotional content (warm parents vs. cold parents). Then, they looked at the associations with a number of key life course variables.Two answers:
- First, having a warm father was associated with almost every positive life course outcome – flourishing in late age, not getting divorced, income. In some cases, the association is striking. In retirement, having a warm parent is associated with tens of thousands of dollars in additional income. That is amazing once you consider that this is an insanely biased sample of male Harvard grads. To push your income even higher in a batch of doctors, executives, and attorneys is stunning.
- Second, stratification variables don’t matter much. In other words, in this sample, having wealthy parents isn’t much of an asset.
- Third, divorce of parents does not seem to matter either once you account for having warm parents and having positive coping strategies.
Bottom line: Social networks seem to be very crucial for the life course. Not for their direct instrumental features (aka social capital), but mainly for allowing people to maintain an emotional composure that allows them to solve problems and thrive.
There is one part of the Apple story that has always puzzled me: what was the difference between Steve Jobs pre-NeXT and post-NeXT? For those who aren’t Appleologists, Steve Jobs was booted from Apple in 1985. He ran a company called NeXT and founded Pixar. NeXT flopped but Pixar succeeded. About ten years later, in 1996, Jobs returned to Apple and steered it into the forefront of computing.
Here’s the thing that puzzled me: What happened in those years? What did he learn or do differently upon his return? I read the Walter Isaacson biography. It is heavy on detail, but light on analysis. You don’t quite understand how he changed in a way that allowed him to reach new heights or resolve old problems. Here are my hypotheses:
- Steve was a little older and a little wiser. He also had more practice from running these two firms which gave him the ability to be more innovative upon returning to Apple. In other words, practice makes perfect. Old people mellow. he worked better with others.
- Nothing changed. Same Steve, but the big difference is that he was completely control of Apple. In Steve Jobs 1, he had other founders to deal with and a board that reflected different groups of stakeholders. In Steve Jobs 2, all the founders were gone and he fired all board members not aligned with him. Thus, his fights with people didn’t undermine the company in the same way Steve Jobs 1 almost ruined Apple. In other words, Apple 1 was a divided firm with different stakeholders and Jobs was not an optimal CEO for such a firm. Apple 2 was built around Jobs and he excelled in that type of environment.
The main evidence for #1 is that he learned a lot from running NeXT that allowed the later Macs to be very successful and his media experience was directly leveraged into the iTunes project. The evidence for #2 is simply that that there is no evidence that Jobs changed as a manager at all over his whole life. The brilliant, but insane, guy you get at Reed in the 1970s is the same guy you get in the 2000s. Your opinion? Show me your work!
This week, I will spend quite a bit of time discussing a book called The Triumphs of Experience by George Vaillant. I’ve written briefly about the book before, but I didn’t appreciate the magnitude of the book until I assigned it for a class. Roughly speaking, the book follows a cohort of college men from the 1940s to the mid 2000s. Thus, the book tracks people from young adulthood to old age. It’s a powerful book in that it uses enormously rich data to analyze the life course and identify factors that contribute to our well being. You won’t find many other books that have such deep data to address one of life’s most important questions – What makes us happy? What is the good life?
In this first post, I want to briefly summarize the book and then note a few drawbacks. Later this week, I want to delve into two topics in more detail: alcoholism and parental bonds. To start: the Grant Study of Human development randomly selected a few hundred male Harvard undergrads for a long term study on health and the life course. It’s a biased sample, but it’s well suited for studying long life and work (remember, many women became home makers in that era) while controlling for educational attainment. The strength of this book is an ability to mine rich qualitative data on the life course and then mapping the associations over decades. The data is rich enough that the authors can actually consider alternative hypotheses and build multi-cause explanations.
A few drawbacks: Rhetorically, I thought the book was a bit wordier and longer than it needed to be. Also, I wish that the book had a glossary or appendix where one can look up definitions. More importantly, this book will note be convincing to folks who are obsessed with identification. It is very “1960s” in that they collect a lot of data and then channel their energies into looking at cross-group differences. But still, considering that doing RCT with your family is not possible and the importance of the data, I’m willing to forgive. Wednesday: The importance of your family.