Workplace learning cultures, learning potential and important work outcomes among managerial employees in five-star Turkish hotels
Bibliographic record
Abstract
This research investigated the relationship of perceived workplace learning culture, workplace learning potential, perceived employability, feelings of psychological empowerment, important work outcomes, and self-reported assessments of service quality among supervisors and managers in five star hotels in Turkey. The goals were to determine the effects of workplace learning cultures on key managerial experiences. Data were collected from 205 managers, an eighty-nine percent response rate, from twelve hotels, using anonymously completed questionnaires in the last quarter of 2014. Work outcomes included job satisfaction, perceptions of service quality and intent to quit. Managerial Self-efficacy was significantly related to perceptions of workplace learning culture, opportunities for learning, employability and all other work outcomes. In addition, stronger workplace learning cultures and more opportunities for learning also had positive effects of several work outcomes. Practical implications of these findings along with future research directions are offered. Practical applications include training supervisors on ways to develop and support a workplace learning culture, training all employees on the benefits of personal efficacy and ways to increase it, and training employees on the benefits of their own learning and ways to enhance this.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".