In Pursuit of Impact: How Psychological Contract Research Can Make the Work-World a Better Place
Bibliographic record
Abstract
This paper is the result of the collective work undertaken by a group of Psychological Contract (PC) and Sustainability scholars from around the world, following the 2023 Bi-Annual PC Small Group Conference (Kedge Business School, Bordeaux, France). As part of the conference, scholars engaged in a workshop designed to generate expert guidance on how to aid the PC field to be better aligned with the needs of practice, and thus, impact the creation and maintenance of high-quality and sustainable exchange processes at work. In accordance with accreditation bodies for higher education, research impact is not limited to academic papers alone but also includes practitioners, policymakers, and students in its scope. This paper therefore incorporates elements from an impact measurement tool for higher education in management so as to explore how PC scholars can bolster the beneficial influence of PC knowledge on employment relationships through different stakeholders and means. Accordingly, our proposals for the pursuit of PC impact are organized in three parts: (1) research, (2) practice and society, and (3) students. Further, this paper contributes to the emerging debate on sustainable PCs by developing a construct definition and integrating PCs with an ‘ethics of care’ perspective.
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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 | 0.112 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.012 | 0.098 |
| Scholarly communication | 0.039 | 0.054 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".