Enhancing Student Compositional Diversity in the Sociology Classroom
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
It is well documented that interaction between diverse students encourages positive learning outcomes. Given this, we examine how to enhance the quantity and quality of student diversity in university classrooms. Drawing on sociological theory linking life experiences with ways of knowing, we investigate how to increase classroom diversity by considering when, where, and how courses are scheduled and delivered. Our focus on structural features of academic scheduling and classroom offerings in relation to compositional diversity is unique, complementing established individual-level approaches for diversity enhancement. Using data from 96 Introduction to Sociology courses offered at the University of British Columbia between 2004 and 2014, we demonstrate that course structure has significant influence on a variety of student diversity measures (age, academic year, student major, country of origin, domestic or international status, and gender). We conclude by discussing ways instructors can employ sociological insights to optimize the pedagogical possibilities and challenges of diverse classrooms.
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 | 0.024 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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