The majority of the class will be made up of reading, discussing, and formal writing. However, there will be informal writings and other assignments just to mix it up. It will be fun.
Some general thoughts on writing.
Please be sure to read Pomona’s Policies on Academic Integrity. Additional information on citation, summarizing, and working with others is provided so that you can successfully maintain academic integrity. You will be held accountable to the standards.
For ideas to get started, the handout on They Say, I Say is incredibly useful.
You may want to look at the peer review guidelines used to provide feedback on your written work.
9/5/21
Consider a time in your life that had a random / chance / fateful
aspect. Describe the scene from the 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.
9/12/21
Believing / Doubting game. Reading Borges with and against the grain,
see
assignment. Paper is due to Sakai by Sunday midnight. As a pdf
document, double spaced, put your name inside the pdf document, no title
necessary.
Don’t forget about the They Say, I Say templates that can be quite helpful in working with written sources.
11/1/21 Post your Dear Data postcards, to discuss in class on 11/4/21
(instructions and thoughts on writing a paper / giving feedback to introductions)
You may be curious about the grading rubric for the formal essays.
Due: 9/16/2021, 9/17/2021, 9/27/2021,
9/30/2021, 10/8/2021
Essay 1
Peer Review
for Essay 1 before class
Peer
Review for Essay 1 in class
Thoughts on writing with a lens text. Also, don’t forget about the They Say, I Say templates that can be quite helpful in working with written sources.
Due: 10/15/2021, 10/21/2021, 11/2/2021
Essay 2
Peer Review
for Essay 2 before class
Peer
Review for Essay 2 in class
Due: 11/11/2021, 11/21/2021, 11/28/2021,
12/10/2021
Essay 3
Peer Review
for Essay 3
handout on annotated bibliographies
Advice on Primary and Secondary Sources by Raimo Streefkerk on Scribbr.
Your final essay 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 essay 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 essay should include:
Some of the founders of the field of statistics were eugenicists. For example, you might start by reading about the journal Nature’s reckoning with their own history supporting eugenics: How Nature contributed to science’s discriminatory legacy, September 2022.
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?
Weapons of Math Destruction (Cathy O’Neil) are 1. opaque, 2. at a large scale, 3. destructive. What WMDs are out there? Wellness programs, employment tests, college applications, credit scores, insurance, etc.
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, Dara Regaignon, and Kara Wittman for ideas and helpful conversations which led to the assignments.
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/hardin47/id1-stats-world, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".