The effects of financial and non-financial incentives on job tenure
Bibliographic record
Abstract
This paper studies the effects of financial and non-financial incentives on job tenure of academics in Jordanian universities. The purpose of this research is to help Jordanian universities find solutions to the job tenure challenge that they face and to explore the role of incentives in job tenure. The study follows the incentives typology of Buchan and incentives are divided into two categories; financial incentive, including salary, other direct financial incentives, and indirect financial incentives, and non-financial incentives including training and education, recreational facilities, occupational health, and flexible working hours, breaks, and sabbatical. Job tenure is measured by the period that the questionnaire respondents were working with the current employers. The study considers two hypotheses and two questions to test the effect of incentives on job tenure. Results show that financial and non-financial incentives had positive significant effects on job tenure. The study recommends universities in Jordan to pay more attention to incentive given to their academics when they aim to increase job tenure.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".