Weighting the Benefits of Part-Time Employment in College: Perspectives from Indigenous Undergraduates
Bibliographic record
Abstract
Although many scholars assert that students’ job involvement is beneficial, there is no consensus on the effect of part-time employment taken by term-time undergraduates. Since more and more indigenous students are participating in part-time employment, and most of them are involved in disadvantaged jobs-longer hours, heavier workload, and smaller salaries, it is getting more important than ever to investigate the effects of their part-time job experiences. This study is thus endeavored to identify the major benefits of part-time jobs performed by indigenous college students, to determine the relative weights of each benefit, and to decide the most beneficial type of part-time job for indigenous college students. A self-developed questionnaire was constructed specifically for this research, and AHP was adopted as the major tool to calculate the relative weights of each benefit. Based on the research results, we highly suggest universities should improve their career counseling platforms, building cooperative relationships with term-time job employers, and offer career related classes to help indigenous students gain most from their off-campus working experiences.
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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 | 0.004 | 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 | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".