Retention of Underrepresented Minority Undergraduates in STEM
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
Far fewer undergraduate students pursue and complete STEM degrees compared to humanities degrees, despite high demand for STEM professionals. Among undergraduate STEM majors, individuals from underrepresented racial minority (URM) groups are far less likely to complete their degree than their White or Asian peers, presenting a serious obstacle to diversity within the STEM workforce. Drawing from Bandura’s Social Cognitive Theory, researchers have identified factors that affect the retention of URM students in STEM, though there is substantial evidence that such factors are moderated by environmental influences not traditionally included in the theory. In this paper, we argue that many environmental influences can be conceptually unified under the State Authenticity as Fit to Environment (SAFE) model. Further, we review literature suggesting that the constructs of both Social Cognitive Theory and the SAFE model interact extensively when considering retention of URM undergraduates, arguing that understanding the interactions between the two models will provide a more complete picture of how retention of URM students can be improved.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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