Envy and future possible selves: Implications for career development
Bibliographic record
Abstract
Social comparisons are ubiquitous, providing information about which goals or outcomes are valued; the performance or behavior required to achieve these; and relative status based on goal and outcome standing. Social comparisons also provoke envy, which influences feelings of inferiority, self esteem and efficacy. We propose that envy does not just affect current working selves, but also future selves. Future possible selves represent personalized goals and are motivational guides promoting proactive career behaviors. We tested a mediation model in two studies with undergraduate business students, a relevant population not least because of the investment that they, their families, and society place on their career preparation. Envy was negatively related to Cantril’s Self Anchoring Scale (1965), which assesses life goal progress 5 years hence, and future possible self. Our second study provided evidence that future self partially mediated the relationship between envy and career decision making self efficacy. Although effects were small, this could be due to small samples and the nature and temporal distance of the future self construct. Nevertheless, we were encouraged by this first exploration into the temporally projected effect of envy on self construal, and discuss implications for students’ career oriented behavior, prospects and well being.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".