Development and Validation of a Short Scale of College Belonging
Bibliographic record
Abstract
Belonging is important for college students’ achievement, persistence, campus engagement, and well-being. There is a great need for a brief measure of college belonging that could be used by researchers and practitioners in field settings. Yet, existing measures of college student belonging are either overly long, lack validation evidence, or have not been psychometrically evaluated to ensure that they are appropriate for students from diverse backgrounds. The goal of this work was to create a short, psychometrically sound scale to measure college students’ sense of belonging. In Study 1, we recruited 392 college students in the U.S. (50% Students of Color; 46% men). Based on their responses, we created a 4-item college belonging scale using confirmatory factor analysis and item response theory methods. In Study 2, we validated this scale in a diverse sample of college students (N = 505; oversampling students of color and sexual minority students) by examining factor structure, measurement invariance, and predictive validity. Collectively, this project advances measurement equity in belonging research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".