PUB TYPE Information Analyses (070) Reports
Bibliographic record
Abstract
Research done during the last 10 years on part-time employment of secondary students was compared with results of a study of part-time employment in Toronto (Ontario, Canada). The literature has indicated that whether part-time work is beneficial or harmful depends on the amount of time students spend at work. In comparison with students with no jobs and students who work long hours, students who work limited hours (up to 15 per week) tended to demonstrate superior academic performance. They tended to spend more time on homework and extracurricular activities and to have lower dropout rates. More than 15 to 20 hours a week was associated with negative academic results. Part time employment among Toronto students was explored through the 1991 Every Secondary Student Survey, the Ontario Provincial assessment of student writing, and a local school survey on the after-school activities of 71 students. Data on Toronto students support the findings of other research. Working was more advantageous to students than not working, provided the hours were moderate (up to. 15 hours a week). Four appendixes present tables that summarize the impact of part-time work on students. (Contains 4 figures and 1 table in the text and 32 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. ssues related to student part-time work: What did research find in the Toronto situation and other context?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.667 | 0.376 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".