The toll of perceived injustice on job search self-efficacy and behavior
Bibliographic record
Abstract
Purpose – Individuals normally make fairness judgements when experiencing negative outcomes on an important task, such as finding employment. Fairness is an affect-laden subjective experience. Perceptions of injustice can cause resource depletion in unemployed job seekers, potentially leading to reduced self-regulation. The purpose of this paper is to investigate the role of: first, justice perceptions during a job search and their impact on job search self-efficacy (JSSE); second, the mediating role of JSSE between justice perceptions and job search strategies; and third, associations between job search strategies and quantity and quality of job search behavior. Design/methodology/approach – Unemployed individuals (n=254) who were actively searching for a job reported on their past job search experiences with respect to justice, completed measures of JSSE, and reported recent job search behavior. Findings – Results reveal the potentially harmful impact of perceived injustice on job search strategies and the mediating role of JSSE, a self-regulatory construct and an important resource when looking for a job. Specifically, perceived injustice is negatively associated with JSSE. Reduced JSSE is associated with a haphazard job search strategy and less likelihood of exploratory and focussed strategies. A haphazard job search strategy is associated with making fewer job applications and poor decision making. Conversely, perceived justice is associated with higher JSSE and exploratory and focussed job search strategies. These two strategies are generally associated with higher quality job search behavior. Research limitations/implications – There are two major limitations. First, while grounded in social-cognitive theory of self-regulation and conservation of resources (COR) theory, a cross-sectional research design limits determination of causality in the model of JSSE as a central social-cognitive mechanism explaining how justice impacts job search strategies. Second, some results may be conservative because social desirability may have restricted the range of negative responses. Practical implications – This study provides insights to individuals who are supporting job seekers (e.g. career counselors, coaches, employers, and social networks). Specifically, interventions aimed at reducing perceptions of injustice, increasing JSSE, and improving job search strategies and behavior may ameliorate the damaging impact of perceived injustice. Originality/value – This study is the first to examine perceived justice in the job search process using social-cognitive theory of self-regulation and COR theory. Moreover, we provide further validation to a relatively new and under-researched job search strategy typology by linking the strategies to the quantity and quality of job search behaviors.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".