Trait gratitude and job search: the mediating role of perceived employability
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the influence of trait gratitude on job search behaviour (preparatory and active) for job seekers approaching graduation. The mediating role of perceived employability is examined. Design/methodology/approach Data were collected from job seekers (n = 143) in their final month of study in two waves with a one-month time lag between first and second data collection. Findings Structural equation modelling analyses revealed that trait gratitude was significantly and positively associated with perceived employability. Perceived employability mediated the relationship between trait gratitude and preparatory job search, but not active job search. Research limitations/implications This study extends research on job search by highlighting the applicability of trait gratitude to the job search process. Practical implications Career counsellors should consider trait gratitude as relevant for program development to address the self-regulation of personal resources during job search. Originality/value This study is the first step towards connecting trait gratitude to the job search literature. The study identifies trait gratitude as a distal personal resource important for self-regulation of a proximal personal resource (i.e. perceived employability) and subsequent job search behaviour.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".