Readings¶
- #8, due Tuesday November 28, 2017:
- Does High Public Debt Consistently Stifle Economic Growth? A Critique of Reinhart and Rogoff, by Herndon, Ash and Pollin.
Also read the following more general interest blog posts:
#7, due Tuesday November 21, 2017: - This blog post and the associated videos on colormaps and matplotlib.
#6, due Monday Novemeber 13, 2017: - The official ASA statement on p-values (asastatementpvalues.pdf on Piazza)
- And two comments on the statement:
- It’s not the p-values’ fault, by Y. Benjamini (asacommybenjamini.pdf on Piazza)
- The value of p-values, by P. Stark (asacommpstark.pdf on Piazza)
- Redefine statistical significance (redefinestatsignat2017.pdf on Piazza)
- If you’re interested you can also read:
- The Problems With P-Values are not Just With P-Values, by A. Gelman (asacommagelman.pdf on Piazza)
- Fit-for-Purpose Inferential Methods: Abandoning/Changing P-values Versus Abandoning/Changing Research, by J. Ioannidis (asacommjioannidis.pdf on Piazza)
- And two comments on the statement:
Prof. Philip Stark will be giving a guest lecture on November 14th on the ASA statement, and it’ll be an interesting discussion.
- #5, due Thursday November 2, 2017:
Reproducible and Replicable Computational Fluid Dynamics: It’s Harder Than You Think, by Olivier Mesnard and Lorena A. Barba. The previous link is to the ArXiV preprint, you can find the final copy on Piazza under “General Resources” in the Resources tab, the file is: mesnard-barba-repro.pdf.
- #4, due Monday October 9, 2017:
- Operationalizing conflict and cooperation between automated software agents in Wikipedia: A replication and expansion of ‘Even Good Bots Fight’, by R. Stuart Geiger (you should read the full PDF available at that address, not just the short summary).
Stuart is an ethnographer at BIDS and will guest lecture in the class on October 10th, talking about this work. You will only need to submit a written report on the above paper. Further information about the lecture follows, you should spend some time exploring the links provided below in order to make the most of Stuart’s presentation.
This lecture will be an inside look into a reproducible research project (repo), which studied conflict between automated software agents (or bots) in Wikipedia. The paper is a bit long and goes into a lot of detail, so feel free to skim. Also spend a little bit of time exploring Wikipedia’s public but behind-the-scenes spaces to get a general background on what bots do and how the community governs them. Try to also get some familiarity with Wikipedia as a version control system, because these commit histories are the primary data analyzed in the study.
- Main materials:
- The paper above, also available here
- Introduction to Wikipedia Bots
- This page contains many links to pages you might find interesting, including a list of bots
- Recent bot edits to English Wikipedia articles – as every page on Wikipedia (including discussion pages) is a flat text file in a version control system.
- Click “diff” on each line to get a diff of what the bot changed
- Click “hist” to see the history of edits to that artcile
- Click the bot’s username to get their profile
- Click “talk” for messages left to the bot’s operator
- Click “contribs” for all the bot’s edits
- Some additional materials if you are interested further:
- The Bot Policy
- ClueBot NG (an anti-spam/vandalism bot using machine learning and neural networks)
- AnomieBOT’s tasklist (a bot account used for many different tasks).
- Double redirects (a task frequently automated with bots that features in the paper).
- Requests for Arbitration: Betacommand 2 (the Arbitration Committee is like Wikipedia’s Supreme Court, this was a controversial case about a bot developer)
- #3, due Monday Sept 25, 2017:
- Treating Code As an Essay, by Yukihiro Matsumoto (aka “Matz”). Matz is the creator of Ruby and the essay talks about Ruby, but its ideas have generic value.
- Python’s Dictionary Implementation: Being All Things to All People, by Andrew Kuchling. An essay that discusses the most important data structure in Python, the Dictionary. In general we will not be diving deeply into technical implementation and programming details, but knowing a little bit about one of the key parts of the language is valuable.
- #2, due Thursday Sept 14, 2017. Three short papers about the scientific Python ecosystem and IPython/Jupyter:
- #1, due Sept 7, 2017: Developing open source scientific practice.