Assignments

Some general thoughts on writing

Please be sure to read Pomona’s Policies on Academic Integrity: http://catalog.pomona.edu/content.php?catoid=7&navoid=394. Additional information on citation, summarizing, and working with others so that you can successfully maintain academic integrity. You will be held to all these standards from this day forward.

Micro-essays (fewer than 500 words)

You may want to look at the peer review guidelines used to provide feedback on your written work.

9/9/2018
Consider a time in your life that had a random / chance / fateful aspect. Describe the scene from this experience (providing any relevant background). The title of your piece should be a single word signifying what you hope to elicit in your reader. Be as free as you like with the topic and style. We will be sharing the writings with our entire ID1 class (they will not be posted publicly), but you will have a chance to revise your essay, if you wish, before they are shared.

9/16/2018
Believing / Doubting game. Reading Borges with and against the grain (see handout). Paper is due to Sakai by Sunday midnight. In Word, double spaced, put your name inside the Word document, no title necessary.

11/7/2018 (Wednesday)
Post your Dear Data postcards, to discuss in class on 11/8/2018

Formal Papers

(instructions and thoughts on writing a paper / giving feedback to introductions)

You may be curious about the grading rubric for the formal papers.

Paper 1

Due: 9/20/2018, 9/25/2018, 10/1/2018, 10/12/2018
Paper 1

Thoughts on writing with a lens text

Peer Review for Paper 1 before class
Peer Review for Paper 1 in class

Paper 2

Due: 10/16/2018, 10/23/2018, 11/4/2018
Paper 2
Peer Review for Paper 2 before class
Peer Review for Paper 2 in class

Paper 3

Due: 11/16/2018, 11/25/2018, 12/2/2018, 12/9/2018
Paper 3

Your final paper will center around a research question (that will become a thesis statement) which will be argued using sources that you find. The research question will continue to evolve over the life of the project, but you should keep coming back to the (evolving) idea you want to argue. The third paper will be a research paper describing how statistics (as a discipline, as a set of data analysis tools, as individual people, etc.) are/were involved in creating or reinforcing systemic inequality or social injustice. In addition to a succinct and arguable thesis statement, your paper should include:

1. Thesis statement somewhere early on and clear to your reader.
2. Details of the event of interest.
3. Historical context ({} the thing you describe happened / was able to happen).
   
4. (Optional) You might also give the reader an idea of possible solutions (how to make it better) or maybe a counter argument.
5. A potential audience for your paper is a STEM undergraduate who feels disempowered by the traditional canon. If your paper speaks to a different audience, please talk to me before turning in your assignments.

Ideas for getting started include:

• Some of the founders of the discipline of statistics were eugenicists.
• Original medical studies were done (almost) entirely on white men.
• 23 & me has information primarily on white, thin, high income Americans. https://podcasts.apple.com/us/podcast/freakonomics-radio/id354668519?i=1000438218337
• Contributions to the field of statistics that were by individuals in marginalized roles were attributed to white men.

• Corollary: because science is dominated by white men, data exist primarily on their contributions. Thus, contributions by non-white men get overlooked. Recently (10/2/2018), Donna Strickland was awarded the Nobel Prize in Physics. Just a few months prior (5/23/2018) Wikipedia refused to allow her page to be created. As reported in The Atlantic, " ‘This submission’s references do not show that the subject qualifies for a Wikipedia article.’ Strickland, it was determined, had not received enough dedicated coverage elsewhere on the internet to warrant a page." https://www.theatlantic.com/science/archive/2018/10/nobel-prize-physics-donna-strickland-gerard-mourou-arthur-ashkin/571909/ [The problem here is about human influence into data and algorithms.]

• The larger issue: current algorithms and AI protocols reinforce existing structures and are often biased against marginalized communities. (Summary and ideas here: https://www.infoq.com/presentations/unconscious-bias-machine-learning.)
• Statistical models were used as part of redlining.
• Tuskegee Study of Untreated Syphilis in the Negro Male or Willowbrook Study.
• Collider bias, e.g., see “Why Statistics Don’t Capture the Full Extent of the Systemic Bias in Policing” by Laura Bronner, https://fivethirtyeight.com/features/why-statistics-dont-capture-the-full-extent-of-the-systemic-bias-in-policing/
• Using “statistics” to show connections between race and disease sets up a structure of biological differences instead of focusing on systemic disparities in healthcare and other socio-economic factors. See “Racial Health Disparities and Covid-19 – Caution and Context” in New England Journal of Medicine https://www.nejm.org/doi/full/10.1056/NEJMp2012910.
• Statistical models used to argue biological determinism (e.g., see The Mismeasure of Man by Stephen Jay Gould and related controversy … http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001071 and http://blogs.nature.com/news/2011/06/did_stephen_jay_gould_fudge_hi.html )

• If scientific knowledge, data-based arguments, and logical & critical reasoning are sound ways of discovery, why were some of the statistics (STEM generally) founders so prone to racist / misogynist / ableist / etc. ideas? That is, what can we know from science and what can we never know from science?

handout on annotated bibliographies

handout on citing sources (Link to the solutions.)

The worksheet was taken directly from the Kean University Library; original source.

Thank you to Vin de Silva, Gizem Karaali, and Dara Regaignon for ideas and helpful conversations which led to these assignments.

Jo Hardin
Pomona College
Class: TuTh 11-12:15, Millikan 2161
email: jo.hardin@pomona.edu
Office Hours: Wed & Thurs 1:30 - 3:30 or by appt

ID1 Intern: Candice Wang
email: ywqi2015@MyMail.Pomona.edu
Office Hours: email Candice to set up a time to meet