A study of the work experience commitments and academic achievements of high school students
Bibliographic record
Abstract
This research outlines a study of the relationship between the part-time work experience commitments and academic achievements of high school students in Alberta's Parkland School Division. Significant research conducted over the past two decades disagrees whether part-time work has adverse effects on student achievement. Economic conditions in Canada have tempted high school students to be employed in various labor roles based on a number of factors. Specifically, this study examines the relationship between the work experience hours and academic achievements of Parkland School Division's secondary school students. The author hypothesizes that when hours of work increase, student achievement decreases. An analysis of the 2009-2010 high school data of work experience hours submitted for high school credits toward attaining a diploma will be compared to student achievement in the School Division's high school, Spruce Grove Composite High. A quantitative investigation by means of a multi-variable regression analysis for each grade level, namely Grade 12, Grade 11, and Grade 10, exhibited no significant correlations among the dependent variables (English, Social Studies, and Mathematics marks) and the independent variable, Work Experience Hours. The results of the research analysis did not support the author's hypotheses that this relationship would be significantly negative and that it would increase in relation to the number of hours worked. The information acquired will be reported to assist Parkland School Division and other school jurisdictions to improve educational programming for secondary students. --Leaf ii.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".