Predictors of Commitment to Careers in the Tourism Industry
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
ABSTRACT The hospitality and tourism industry is a significant contributor to the economies of many countries. As a result, countries need an educated, skilled and committed workforce to be successful. To fill this need, colleges and university have developed programs of study to improve the quality of human resources working in this industry. This study considers predictors of comment to a career in hospitality and tourism among 640 male and 375 female university tourism students in Turkey. Three types of predictors were examined using hierarchical regression analyses: work values, levels of student engagement during their program of study, and levels of student burnout during their university studies. Work values were unrelated to commitment to a career in hospitality and tourism; students' reporting higher levels of engagement, and those reporting lower levels of burnout, were more committed to careers in tourism. Implications of these findings for university tourism programs and employers of graduates of university tourism programs are offered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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