Academic psychological capital: Implications for organizational crises
Bibliographic record
Abstract
Abstract This study examines the role of academic psychological capital (PsyCap) in buffering the negative impact of organizational crises (COVID‐19 pandemic) on educational outcomes in higher education institutions. Drawing on positive organizational behavior theory and crisis management literature, we hypothesize that students with higher levels of academic PsyCap will have significantly higher retention and graduation rates during the crisis, and that academic PsyCap is a better predictor of these outcomes than traditional predictors such as high school GPA and standardized test scores (Scholastic Assessment Test (SAT)). Using a longitudinal approach, we found that academic PsyCap is positively related to 1‐year retention and graduation rates. Academic PsyCap also explains additional variance in these outcomes beyond high school GPA. The findings highlight the importance of cultivating psychological resources like hope, efficacy, resilience, and optimism to promote student success and well‐being during challenging times.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".