<i>Ex ante</i>i-deals, perceived external prestige and turnover intentions
Bibliographic record
Abstract
Purpose The purpose of this paper is to conceptualize ex ante idiosyncratic deals (or i-deals) as a way to foster individual perceptions of a positive employer image by offering customized additional instrumental benefits. Design/methodology/approach A survey is led among 182 engineers in demand on a local labor market to test whether ex ante i-deals combine to a more global and external perception of a good employer, measured by perceived external prestige (PEP), to explain turnover intentions. Findings The results validate all research hypotheses, and show that the moderating effect of ex ante i-deals in the PEP-turnover intention relationship is significant during the first years spent in the company. Originality/value This research contributes to the literature on employees’ attraction and retention by building bridges between the literatures on employer image and i-deals.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".