Agree to disagree lecture series

README.md

@@ -88,7 +88,7 @@ Tue, Nov 15 | [Social network analysis (part I)](pages/nov15-sna-pt1.md) | [slid
 Thu, Nov 17 | [Social network analysis (part II)](pages/nov17-sna-pt2.md) | [slides](slides/20-social-networks-2.pdf) • [video](https://youtu.be/LeRhO2QUZaU)
 Tue, Nov 22 | [Diff-in-diff + CausalImpact](pages/nov22-diff-in-diff.md) | [slides](slides/21-diff-in-diff.pdf) • [video](https://youtu.be/IZXPdvceOZQ)
 ~~Thu, Nov 24~~ | ~~Thanksgiving, no class~~ |
-Tue, Nov 29 | Research vs researcher |
-Thu, Dec 1 | Agree to disagree |
+Tue, Nov 29 | [Research vs researcher](pages/nov29-research-vs-researchers.md) | [video](https://youtu.be/q83a9O3WY2Q)
+Thu, Dec 1 | [Agree to disagree](pages/dec01-agree-to-disagree.md) | [video](https://youtu.be/nE0AHonCsWA)
 Tue, Dec 6 | Final presentations (part I) |
 Thu, Dec 8 | Final presentations (part II) |

pages/dec01-agree-to-disagree.md

@@ -0,0 +1,13 @@
+## L23: Agree to Disagree (no instructor slides, [video](https://youtu.be/nE0AHonCsWA))
+
+
+In this lecture we continue to reflect on how the (empirical) methods, regardless of how rigorously the studies are done, are ultimately applied and interpreted by human researchers. And how interpretation of even hard numbers is inherently subjective, subject to the beliefs, values, politics, social norms, culture, etc of the researchers.
+
+
+### Lecture Readings
+
+> Shepperd, M., Bowes, D., & Hall, T. (2014). [Researcher bias: The use of machine learning in software defect prediction](https://eprints.lancs.ac.uk/id/eprint/127414/1/Bias.pdf). IEEE Transactions on Software Engineering, 40(6), 603-616.
+
+> Ray, B., Posnett, D., Filkov, V., & Devanbu, P. (2014). [A large scale study of programming languages and code quality in GitHub](http:https://baishakhir.github.io/uploads/fse2014-lang_study.pdf). In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (pp. 155-165).
+
+> Berger, E. D., Hollenbeck, C., Maj, P., Vitek, O., & Vitek, J. (2019). [On the impact of programming languages on code quality: a reproduction study](https://dl.acm.org/doi/fullHtml/10.1145/3340571). ACM Transactions on Programming Languages and Systems (TOPLAS), 41(4), 1-24.

pages/nov29-research-vs-researchers.md

@@ -0,0 +1,13 @@
+## L22: Separate the Research From the Researcher? (no instructor slides, [video](https://youtu.be/q83a9O3WY2Q))
+
+
+In this lecture we reflect on how the (empirical) methods, regardless of how rigorously the studies are done, are ultimately applied and interpreted by human researchers. And how interpretation of even hard numbers is inherently subjective, subject to the beliefs, values, politics, social norms, culture, etc of the researchers.
+
+
+### Lecture Readings
+
+> Breznau, N., Rinke, E. M., Wuttke, A., Adem, M., Adriaans, J., Alvarez-Benjumea, A., ... & van der Linden, M. (2021). [Observing Many Researchers using the Same Data and Hypothesis Reveals a Hidden Universe of Data Analysis](https://osf.io/preprints/metaarxiv/cd5j9/download).
+
+> Shepperd, M., Bowes, D., & Hall, T. (2014). [Researcher bias: The use of machine learning in software defect prediction](https://eprints.lancs.ac.uk/id/eprint/127414/1/Bias.pdf). IEEE Transactions on Software Engineering, 40(6), 603-616.
+
+> AlShebli, B., Makovi, K., & Rahwan, T. (2020). [RETRACTED ARTICLE: The association between early career informal mentorship in academic collaborations and junior author performance](https://www.nature.com/articles/s41467-020-19723-8).). Nature Communications, 11(1), 1-8.