Antecedents of perceived overqualification: a three-wave study
Bibliographic record
Abstract
Purpose – The purpose of this paper is to investigate the role of job search on perceived overqualification by applying the theory of planned behavior and including financial need and openness to experience as moderators. Design/methodology/approach – Three questionnaires were given at weeks 1, 8 and 12 to 436 practice firm participants. A total of 119 completed all three questionnaires. The authors used partial least squares to analyze the data. Findings – Job search self-efficacy was positively related to job search intentions and to outcome expectations. Job search intentions were positively related to job search intensity. Financial need acted as a moderator of the relationship between job search intensity and perceived overqualification such that for those with high-financial need higher levels of job search intensity resulted in higher perceived overqualification. Research limitations/implications – The authors found little support for the theory of planned behavior in the model. The authors found strong support for the role of job search self-efficacy and job search intentions. The use of a three-wave design resulted in a relatively low sample size and the use of the practice firm reduces the generalizability of the findings. Practical implications – The results suggest that increasing job search self-efficacy and job search intentions while managing the anticipations of job seekers is likely to yield better job search outcomes. Originality/value – This study investigates the role of job search on perceived overqualification. Findings suggest that malleable attitudes during job search such as job search self-efficacy, job search intentions, and anticipations are likely to impact perceived overqualification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".