The Effects of Part-Time Faculty on First Semester Freshmen Retention: A Predictive Model Using Logistic Regression
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
Part-time faculty clearly serve a valuable purpose in higher education; however, their increased use raises concerns for administrators, faculty, and policy makers. Part-time faculty members spend a greater proportion of their overall time teaching, but the initial evidence suggests that these instructors are less available to students and are less engaged with the campus environment. Recent research attempts to connect part-time faculty utilization to student outcomes. This study explored the effects of exposure to part-time faculty instruction on student retention. Typical first-year students entering the study institution between 1999 and 2003 received over one-quarter of their total first-year instruction from part-time faculty. Furthermore, results show that as exposure to part-time faculty instruction increases, the odds of being retained decrease. Because the use of part-time faculty varies based on institutional type, additional research should focus on diverse institutional settings.
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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 | 0.022 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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