The Role of Social Group Membership on Classroom Participation
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
ABSTRACT Active and cooperative learning is integral to many social science classes, as it increases student motivation, improves communication skills, and stimulates creative thinking. Many political science departments break large lectures down into smaller, weekly tutorial groups to foster active learning. But do all students participate equally in active, participatory learning? We use an original dataset measuring self-reported participation and a number of important predictors (student gender, race, and language proficiency) collected from 700 undergraduate students in 91 political science tutorials. We find that participation does vary across social groups, even when controlling for psychological and some contextual factors. Female students participate significantly less than males, racial minorities report speaking less frequently than white students, and students with lower English-proficiency (the language of instruction) also participate less. In light of these findings, we offer suggestions for instructors on how to motivate all students to find their voice in the classroom.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| 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