The Influence of High-Involvement Human Resources Practices, Procedural Justice, Organizational Commitment, and Citizenship Behaviors on Information Technology Professionals' Turnover Intentions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present study investigates the relationships between a multidimensional, theoretically grounded configuration of high-involvement human resources (HR) practices and turnover intentions. Precisely, it addresses two research questions: What high-involvement HR practices are needed to implement an effective strategy for retaining highly skilled professionals? Do procedural justice, organizational commitment, and citizenship behaviors mediate the effects of high-involvement HR practices on turnover intentions? A survey instrument containing previously validated measures was developed and sent to Quebec members of the Canadian Information Processing Society. Data from 394 respondents were used to test the research model. Key findings reveal that nonmonetary recognition and competency development, and, to a lesser extent, fair rewards and information-sharing practices, are negatively and directly related to turnover intentions. The authors also observed that procedural justice, affective and continuance commitment, and citizenship behaviors partially mediate the effects of high-involvement HR practices on the turnover intentions of highly skilled professionals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it