Nature, predictors, and outcomes of the psychological capital trajectories observed among upcoming police officers' undergoing vocational training
Bibliographic record
Abstract
This study seeks to achieve a dynamic person-centered understanding of the nature of the psychological capital trajectories observed among upcoming police officers undergoing vocational training. Moreover, it seeks to document the predictive role of leader-member exchange and perceived organizational support in relation to these psychological capital trajectories, as well as the implications of these trajectories for a variety of outcomes related to trainees' attitudes (i.e., organizational cynicism, identification with the organization, engagement in the training program, and satisfaction toward the training program), psychological health (i.e., perceived stress), and behaviors (i.e., performance in the training program). A sample of 1200 participants undergoing a 33-week full-time vocational training program to become police officers were surveyed four times over a period of five months and a half. Results revealed that psychological capital trajectories corresponded to five primary profiles: Learning to Hate, High Fit, Moderate Fit, Honeymoon-Hangover, and Low Fit. Perceived leader-member exchange and organizational support were associated with these trajectories in a way that mainly supported our expectations. Trajectories characterized by lower levels of psychological capital were associated with higher levels of cynicism and stress, and with lower levels of engagement, identification, performance, and satisfaction. Conversely, trajectories characterized by higher levels of psychological capital were associated with the most positive outcomes. • We found five profiles of trainees presenting various trajectories of psychological capital. • Three of these profiles were highly stable over time. • Trajectories with lower psychological capital were associated with the worst outcomes. • Trajectories with higher psychological capital were associated with the most positive outcomes. • Increases in LMX and perceived organizational support had positive effects on psychological capital
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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; 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".