An Elephant in the Room: Bias in Evaluating a Required Quantitative Methods Course
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Undergraduate Political Science programs often require students to take a quantitative research methods course. Such courses are typically among the most poorly rated. This can be due, in part, to the way in which courses are evaluated. Students are generally asked to provide an overall rating, which, in turn, is widely used by students, faculty, and administrators to assess a course. Unfortunately, even questions composed with the best of intentions have the potential to bias the results. In this article, we evaluate the global rating question used at our university and show that it introduces bias into the measure by cuing extraneous considerations. It artificially inflates the number of negative reactions to the course by leading students to think about its required status and their initial level of enthusiasm rather than their level of accomplishment and its value as a learning experience. By locating our results in the course evaluation and framing literature, we suggest an approach to evaluating overall rating questions that can be adapted for use at other institutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.165 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it