Development idiosyncratic deals and career success
Bibliographic record
Abstract
Purpose – The purpose of this paper is to rely on the sponsored-mobility perspective of career success (Turner, 1960) to explore the antecedents and consequences of development idiosyncratic deals (i-deals). The authors position career planning as an antecedent of development i-deals, and subjective and objective measures of career success as an outcome. Design/methodology/approach – The authors led a two-wave study among a sample of 325 engineers to test the research hypotheses. Findings – Results support the hypotheses. Development i-deals are positively related to three objective measures of career success (e.g. promotions, hierarchical level, and salary) and one subjective measure of career success (e.g. career satisfaction). Practical implications – The results offer new perspectives to practitioners who want to better manage the careers of their talented employees by highlighting the positive effects of development i-deals on career success. Originality/value – This paper relates i-deals to the field of careers.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".