Recommendations of the Week: June 4-10

Book

I was supposed to read Wanderlust for my first year seminar, but it ended up being one of the first school assignments I did not fully complete. Three years later, my next creative writing teacher recommended A Field Guide to Getting Lost to all of us new graduates. I read it, my first Rebecca Solnit book, at the end of March this year. I immediately wanted to read everything Solnit had ever written, and shipped The Faraway Nearby home so my mother could bring it with her to France. I’m 50 pages from the end now and, like all her books, it’s a wondrous journey across many geographies, stories, and histories.

“Fairy tales are children’s stories not in who they were made for but in their focus on the early stages of life, when others have power over you and you have power over no one.

In them, power is rarely the right tool for survival anyway. Rather the powerless thrive on alliances, often in the form of reciprocated acts of kindness – from beehives that were not raided, birds that were not killed but set free or fed, old women who were saluted with respect. Kindness sewn among the meek is harvested in crisis.”

From the internet

The LSE Impact Blog shared a fun way to spread academic learnings to a wider audience: comics!

“By turning research into an illustrated abstract it’s possible to make academic work more accessible to a non-technical audience and people outside of the discipline. Alpa and Karen have even been approached by an author who would like to include the image in a forthcoming anthropology textbook, while Alpa hopes the article will also reach students, other academics and even non-academics, to explain the value of anthropology and long-term participant observation.”

Podcast

My mother and I listened to “Episode 77: Kalevala (with Elena Varg)” from Spirits on the train to Versailles. The Finnish epic is bonkers, featuring birds nesting on the limbs of goddesses, the Devil’s own personal petting zoo, badass mothers, and a river of death. Elena Varg’s accent is wonderful and her excitement for the story makes this one of my favorite Spirits episodes ever.

Kinda creepy, kinda cool

“Food”

Haribos Sour Rainbow Strips are one of a variety of rainbow-colored, sour/sugar-coated gummy candies, nearly all of which I love. While other brands can be too licorice-flavored, gummy, sweet, or unwieldly, Haribos’ colors can easily be stripped apart and each belt of tart candy is mouthwatering. Unfortunately unavailable in Nairobi. I should have brought more than one bag back from France, since I’ve already devoured the one I did bring.

A knock-off version of my new favorite sour gummies

Watch Them Again

You can really see the drawings behind the animation in the original Lion King movie. Rafiki is more bonkers than I remembered, and Nala a more beautiful lioness.

Also watched some Modern Family in the evenings with my mother on our vacation. Like most family drama/comedy shows I love (see also Reba), everyone makes mistakes and is flawed but they choose to do the right thing in the end. Heartwarming and cozy, with lots of silly in between.

I hadn’t seen the more recent seasons where the kids are older.

Grounded Theory, Part 1: What is it?

Photo by Calum MacAulay on Unsplash

I recently read Brené Brown’s Daring Greatly. The book presents Brown’s research, but it can feel more like a personal guidebook to tackling issues of vulnerability and shame.

Because the research has a conversational feel, it’s hard to understand how much of the book is based in research and how much in Brown’s individual experiences. She weaves in personal stories frequently, often to demonstrate a prickly emotional experience that was common across her interviews. But when I reached the end of the book, I wanted to know how she drew these theories from the data. I’ve only worked sparingly with qualitative data: how does one “code” qualitative data? How do you analyze it without bringing in all sorts of personal biases? How do you determine its replicability, internal and external validity, and generalizability?

Ingeniously, Brown grounds the book in her research methods with a final chapter on grounded theory methodology. Her summary (also found online here) was a good introduction to how using grounded theory works and feels. But I still didn’t “get” it.

So I did some research.

Grounded Theory

Brown quotes 20th century Spanish poet Antonio Machado at the top of her research methods page:

“Traveler, there is no path. / The path must be forged as you walk.”

This sentiment imbued the rest of the grounded theory (GT) research I did. Which seemed bizarre to a quant-trained hopeful economist. I’m used to pre-analysis plans, testing carefully theorized models, and starting with a narrow question.

Grounded theory is about big questions and a spirit of letting the data talk to you.

Founded by Barney Glaser and Anselm Strauss in 1967, GT is a general research methodology for approaching any kind of research, whether qual- or quant-focused. When using GT, everything is data – your personal experiences, interviews, mainstream media, etc. Anything you consume can count, as long as you take field notes.

Writing field notes is one of the key steps of GT: coding those notes (or the data themselves – I’m still a little blurry on this) line-by-line is another. The “codes” are recurring themes or ideas that you see emerging from the data. It is a very iterative methodology: you collect initial data, take field notes, code the notes/data, compile them into memos summarizing your thoughts, collect more data based on your first learnings, code those, compile more memos, collect more data…

Throughout the whole process, you are theorizing and trying to find emergent themes and ideas and patterns, and you should actively seek new data based on what your theories are. You take a LOT of written notes – and it sounds like in the Glaserian tradition, you’re supposed to do everything by hand. (Or is it just not using any algorithms?)

Brown describes the data she collected and her coding methodology:

“In addition to the 1,280 participant interviews, I analyzed field notes that I had taken on sensitizing literature, conversations with content experts, and field notes from my meetings with graduate students who conducted participant interviews and assisted with the literature analysis. Additionally, I recorded and coded field notes on the experience of taking approximately 400 master and doctoral social-worker students through my graduate course on shame, vulnerability, and empathy, and training an estimated 15,000 mental health and addiction professionals.

I also coded over 3,500 pieces of secondary data. These include clinical case studies and case notes, letters, and journal pages. In total, I coded approximately 11,000 incidents (phrases and sentences from the original field notes) using the constant comparative method (line- by- line analysis). I did all of this coding manually, as software is not recommended in Glaserian-grounded theory.” [emphasis mine]

The ultimate goal is to have main concepts and categories emerge from the data, “grounded” in the data, that explain what main problem your subjects are experiencing and how they are trying to solve that problem. For example, Brown’s work centers on how people seek connection through vulnerability and try to deal with shame in various health and unhealthy ways. She started with this big idea of connection and just started asking people about what that meant, what issues there were around it, etc. until a theory started to arise from those conversations.

You’re not supposed to have preexisting hypotheses, or even do a literature review to frame specific questions, because that will bias how you approach the data. You’re supposed to remain open and let the data “speak to you.” My first instinct on this front is that it’s impossible to be totally unbiased in how you collect data. Invariably, your personal experience and background determine how you read the data. Which makes me question – how can this research be replicable? How can a “finding” be legitimate as research?

My training thus far has focused on quantitative data, so I’m primed to preference research that follows the traditional scientific method. Hypothesize, collect data, analyze, rehypothesize, repeat. This kind of research is judged on:

  • Replicability: If someone else followed your protocol, would they get the same result?
  • Internal validity: How consistent, thorough, and rigorous is the research design?
  • External validity: Does the learning apply in other similar populations?
  • Generalizability: Do the results from a sample of the population also apply to the population as a whole?

GT, on the other hand, is judged by:

  • Fit: How closely do concepts fit the incidents (data points)? (aka how “grounded” is the research in the data?)
  • Relevance: Does the research deal with the real concerns of participants and is it of non-academic interest?
  • Workability: Does the developed theory explain how the problem is being solved, accounting for variation?
  • Modifiability: Can the theory be altered as new relevant data are compared to existing data?

I also read (on Wikipedia, admittedly), that Glaser & Strauss see GT as never “right” or “wrong.” A theory only has more or less fit, relevance, workability, or modifiability. And the way Brown describes it, I had the impression that GT should be grounded in one specific researcher’s approach:

“I collected all of the data with the exception of 215 participant interviews that were conducted by graduate social-work students working under my direction. In order to ensure inter-rater reliability, I trained all research assistants and I coded and analyzed all of their field notes.”

I’m still a bit confused by Brown’s description here. I didn’t know what inter-rater reliability was, so I had assumed it meant that the study needed to have internal consistency in who was doing the coding. But when I looked it up online, it appears to be the consistency of different researchers to code the same data in the same way. So I’m not sure how having one person do all of the research enables this kind of reliability. Maybe if your GT research is re-done (replicated) by an independent party?

My initial thoughts are that all GT research sound like they should have two authors that work in parallel but independently, with the same data. Each develops separate theories and then at the end, the study can compare the two parallel work streams to identify what both researchers found in common and where they differed. I still have a lot of questions about how this works, though.

Lingering Questions

A lot of my questions are functional. How do you actually DO grounded theory?

  • How does GT coding really work? What does “line-by-line” coding mean? Does it mean you code each sentence or literally each line of written text?
  • Do these ever get compiled in a database? How do you weight data sources by their expertise and quality (if you’re combining studies and interviews with average Joes, do you actively weight the studies)? -> Can you do essentially quantitative analysis on a dataset based on binary coding of concepts and categories?
  • How do you “code” quantitative data? If you had a dataset of 2000 household surveys, would you code each variable for each household as part of your data? How does this functionally work?
  • If you don’t do a literature review ahead of time, couldn’t you end up replicating previous work and not actually end up contributing much to the literature?

And then I also wondered: how is it applicable in my life?

  • Is GT a respected methodology in economics? (I’d guess not.)
  • How could GT enhance quant methods in econ?
  • Has GT been used in economic studies?
  • What kinds of economic questions can GT help us answer?
  • Should I learn more about GT or learn to use it in my own research?

Coming up: Part 2, Grounded Theory & Economics

To answer some of my questions, I want to do an in-depth read of a paper from the 2005 Grounded Theory Review by Frederick S. Lee: “Grounded Theory and Heterodox Economics.” (The journal has another article from 2017 entitled “Rethinking Applied Economics by Classical Grounded Theory: An invitation to collaborate” by Olavur Christiansen that I hope to read, too.)

2018 Book Challenge

A snapshot of my current “unread” shelf

I wanted to read more in 2018. I also wanted to read some classic lit that my education has neglected to this point.

So I decided to read 52 books in 2018. I’m at 12, including a few books from 2017 I snuck in there since I read them after deciding to do the challenge.

Read:

Week Title Author Date Started Date Finished
Dec 31 Lolita Vladimir Nabokov Oct. 15, 2017 Dec. 13, 2017
Jan 7 American Gods Neil Gaiman Nov. 16, 2017 Nov. 19, 2017
Jan 14 The Curious Incident of the Dog in the Night Mark Haddon Nov. 23, 2017 Nov. 25, 2017
Jan 21 Jane Eyre Charlotte Bronte Dec. 17, 2017 Dec. 20, 2017
Jan 28 Woman at Point Zero Nawal El Saadawi Dec. 21, 2017 Dec. 22, 2017
Feb 4 Doing Good Better William MacAskill Jan. 28, 2018 Feb. 10, 2018
Feb 11 Turtles All the Way Down John Green Feb. 1, 2018 Feb. 1, 2018
Feb 18 The Fifth Season N. K. Jemisin Feb. 2, 2018 Feb. 3, 2018
Feb 25 La Belle Sauvage Philip Pullman Feb. 9, 2018 Feb. 9, 2018
Mar 4 Red Queen Victoria Aveyard March 16, 2018 March 17, 2018
Mar 11 A Field Guide to Getting Lost Rebecca Solnit March 29, 2018 April 3, 2018
Mar 18 Daring Greatly Brene Brown April 4, 2018 April 14, 2018

To read:

Mar 25 The Power Naomi Alderman
Apr 1 The Unbearable Lightness of Being MIlan Kundera April 16, 2018
Apr 8 The Girls (?) Emma Cline April 7, 2018
Apr 15 Poor Economics
Esther Duflo & Abhijit Banerjee
 (years ago)
Apr 22 Thinking, Fast and Slow Daniel Kahneman Feb. 18, 2018
Apr 29 Her Body and Other Parties Carmen Maria Machado
May 6 The Faraway Nearby Rebecca Solnit
May 13 Wanderlust Rebecca Solnit
May 20 1984 George Orwell
May 27 If On a Winter’s Night A Traveler Italo Calvino
Jun 3 A Room of One’s Own Virginia Woolf
Jun 10 Franny and Zooey J. D. Salinger
Jun 17 Capital in the Twenty-First Century Thomas Picketty
Jun 24 To the Lighthouse Virginia Woolf
Jul 1 The Hitchhiker’s Guide to the Galaxy Douglas Adams
Jul 8 Notorious RBG: The Life and Times of Ruth Bader Ginsburg Irin Carmon
Jul 15 The Core of the Sun Joanna Sinisalo
Jul 22 The Dead James Joyce
Jul 29 The Ethical Slut: A Guide to Infinite Sexual Possibilities Dossie Easton
Aug 5 Midnight’s Children Salman Rushdie
Aug 12 Catch-22 Joseph Heller
Aug 19 Anna Karenina Leo Tolstoy
Aug 26 Mountains Beyond Mountains Tracy Kidder
Sep 2 The Metamorphosis Kafka
Sep 9 Slaughterhouse Five Kurt Vonnegut
Sep 16 Song of Solomon Toni Morrison Dec. 20, 2017
Sep 23 Why Nations Fail Acemoglu & Robinson
Sep 30 Neverwhere Neil Gaiman
Oct 7 Lord of the Flies William Golding
Oct 14 Daughters of the North Sarah Hall
Oct 21 The Captain Class (?) Sam Walker
Oct 28 The Obelisk Gate N. K. Jemisin
Nov 4 The Stone Sky N. K. Jemisin
Nov 11 Binti Nnedi Okorafor
Nov 18 As Eve Said to the Serpent Rebecca Solnit
Nov 25 The Mother of All Questions Rebecca Solnit
Dec 2 Hope in the Dark Rebecca Solnit
Dec 9 The Challenge for Africa Wangari Maathai
Dec 16 A Paradise Built in Hell Rebecca Solnit
Dec 23 The Signature of All Things (?) Elizabeth Gilbert

 

Will most likely keep moving things around and taking books on and off the list, but it’s an outline.

Year wrap-up

In total, I read 37 books over my 2018+ “year” of reading. An awesome increase from previous years.

The additional books I ended up reading:

Title Author Date finished
The Faraway Nearby Rebecca Solnit June 8, 2018
The Two Princesses of Bamarre Gail Carson Levine June 12, 2018
The Power Naomi Alderman July 10, 2018
Love in the Time of Dragons Katie MacAlister July 11, 2018
The Story of O Anne Desclos July 14, 2018
The Obelisk Gate N. K. Jemisin July 15, 2018
Her Body and Other Parties Carmen Maria Machado July 23, 2018
Glass Sword Victoria Aveyard July 31, 2018
What Got You Here Won’t Get You There Marshall Goldsmith August 5, 2018
The Stone Sky N. K. Jemisin August 8, 2018
Who Fears Death Nnedi Okorafor August 16,2018
Binti Nnedi Okorafor August 18, 2018
What Sunny Saw in the Flames Nnedi Okorafor August 21, 2018
Lagoon Nnedi Okorafor August 23, 2018
On Writing Stephen King September 3, 2018
Lady Chatterley’s Lover D. H. Lawrence September 16, 2018
Bad Feminist Roxane Gay September 26, 2018
The Wife Meg Wolitzer September 26, 2018
An Untamed State Roxane Gay September 29, 2018
Avalon High: The Merlin Prophecy Meg Cabot September 29, 2018
Kingdom of Ash Sarah J. Maas November 4, 2018
Succubus Dreams Richelle Mead November 25, 2018
King’s Cage Victoria Aveyard December 1, 2018
Deep Work Cal Newport December 8, 2018
The Power of Habit Charles Duhigg December 18, 2018