developerliberationfront / exploringghtorrent Goto Github PK

• Emerson makes Clarissa an account
• Clarissa downloads MySQL Workbench
• Clarissa finds some interesting tables and browses the data

This issue should probably be broken down, but it'll stand in so we remember to do it. The paper is due in June, if memory serves.

The paper discusses the impact of female scientists choosing to leave a profession in order to have children on the number of women who are assistant/associate/full professors in the science and math-based fields. I'm using the ideas expressed in this paper to consider recent statistics that were discovered by the team: seemingly more men than women have pictures of their children on their GitHub accounts.

Williams, Wendy M., and Stephen J. Ceci. "When Scientists Choose Motherhood." American Scientist 100.2 (2012): 138-45. Student Research Center. Web. 7 Jan. 2016.

Current Plan:
Look in table female_first_pulls of Sandbox - match the pull_request_id with pull_request_id from table pull_request_history
Save the pull_request_id and created_at of instances where action "closed" exists
Match the pull_request_id from pull_request_history with pull_request_id from pull_requests
Save the base_repo_id or head_repo_id for each of these _pull_request_id_s from pull_requests
Look in pull_request_history for instances where actor_id equals user_id from female_first_pulls after the created_at date saved from pull_request_id
For the above instances, save the pull_request_id
Go to pull_requests and see if this pull_request_id has the same head/base repo id. If yes, count the instances of this match

Go through this tutorial:
http://www.w3schools.com/sql/

Last week I read both the papers on facial structure and gender discussed in the Slack group (the one I originally shared, and the second paper shared by Andrew), to determine which paper would be best suited for the needs we have in our research papers.

The paper I shared, "What gives a face its gender?" by Elizabeth Brown and David I Perrett, outlines an experiment in which prototypes of female and male facial features were generated and then isolated from the face to determine which features provided the most information about a person's gender. This research indicated that the jaw gives the most significant information about gender. However, the data that is more relevant is not the research itself but the facts presented in the introduction: the female nose is smaller, wider, and more concave, with a depressed bridge, and the female has a smaller mouth and a less pronounced jawline and brow ridge. Female cheekbones are also more rounded (this information can be found in the final two paragraphs of page 829 - the first page of the paper).

The paper Andrew shared, "The Intersection of Gender-Related Facial Appearance and Facial Displays of Emotion" by Reginald B. Adams, Jr., Ursula Hess, and Robert E. Kleck, examines the connections between gender stereotypes and displays of emotion between the genders. Though this paper does cite the information from the paper I shared, it is only in a brief and vague two sentences (page 8, under "Confound between gender appearance and facial maturity"). The 1993 paper provides much more detail and insight into the specific facial features that indicate gender, whereas this paper focuses more on expression and social constructs.

What Gives a Face Its Gender?
The Intersection of Gender-Related Facial Appearance and Facial Displays of Emotion

• Take a look at the existing paper
• Brainstorm some questions, and write them here

@CaptainEmerson
I found a paper that researches various methods to infer gender from names in data. It's pretty brief, but the conclusion is mostly what drew my eye: "the performance of name-based gender detection approaches varies according to the country of origin...Significant enhancements can be achieved by combining name-based with image-based gender detection methods."
Might be helpful when you're considering the methods we used w/ facial recognition or the perception of gender?

Here's a table w/ a summary of the accuracy of the various methods they used.

Just realized that I finished writing the notes for this and never submitted it as an issue.
Paper is here
A compilation of four studies that examined how the surrounding environment can influence women's perceptions of their relation to computer science. Though this paper focused on the physical environment, I am using it to consider the effects of a digital environment, such as the interactions on GitHub.

The idea I mentioned briefly of the presentation of politeness ("Thanks!" versus "Thanks.") was generated by this paper. I'm in the process of examining the patterns between the variations of thank you and considering other instances where the interactions of the digital environment could be discouraging.