Bibliographic record
Abstract
Purpose The purpose of this paper is to address and gain a more complete understanding of the effects on relationships between perceived team support (PTS), team commitment and intent to leave the team. Design/methodology/approach Team commitment was examined as a mediator between perceived team support and intent to leave the team. To reach this objective, a survey on French white‐collar employee (n=355) was conducted. The procedure of Baron and Kenny was selected for the mediation test. Findings The study provides several interesting data. First, data reveal two dimensions for PTS. The first one is labelled PTS toward work, the second one is labelled PTS toward well‐being. Second, while team commitment mediates the relationship between PTS toward work and intent to leave the team, team commitment does not mediate PTS toward well‐being and the intent to leave the team. Originality/value The findings extend the understanding of how perceived team support and team commitment are related to intent to leave the team. It was found that team commitment plays a mediating role between perceived team support and intent to leave the team. Because to date, no research has examined the mediating role of team commitment on the relationship between PTS and intent to leave the team, the study provides interesting findings.
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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 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".