Exploring Individual and Interpersonal Level Factors Associated with Academic Success of College Students at a Women’s, Faith-based Higher Institution
Bibliographic record
Abstract
The present study investigated how spirituality, peer connections, and social integration relate to academic resiliency, academic self-efficacy, academic integration, and institutional commitment of college students who identify as female. A sample of 372 undergraduates (ages 18-26) at a Catholic University completed Mapworks survey containing institution-specific questions and spirituality items in Spring 2018. Pearson correlation was used to examine the bivariate relationships between the variables. Canonical correlation analysis (CCA) was conducted to determine if relationships exist among the predictor variables (spirituality, peer connections, social integration) and the criterion variables (academic resiliency, academic self-efficacy, academic integration, institutional commitment). Academic resiliency was the only contributor to the synthetic criterion variable. The contributions of academic self-efficacy, academic integration and institutional commitment to the synthetic criterion variable were very negligible. Social integration and peer connections were the primary contributors to the predictor synthetic variable, with a secondary contribution by spirituality. Social integration, peer connections, and spirituality were all positively related to academic resiliency. Simultaneously addressing the social and spiritual well-being of college students, particularly those who have self-selected to attend a women’s college, are crucial to promoting their academic success.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".