Benefits of providing supports for non-traditional students to access and complete post-secondary education
Bibliographic record
Abstract
This study explored the benefits of providing supports to non-traditional students in accessing and completing post-secondary education. It focused on one access program, the Winnipeg Education Centre - Social Work Program (WEC-SWP). The purpose of this study was to gain insight into the following questions: (1) What supports at the WEC-SWP assisted non-traditional students in accessing and completing post-secondary education? (2) What benefits did these students acquire by completing a post-secondary degree? Identify personal, professional, economic, community, and society benefits. In addition, the research explored the barriers non-traditional students faced in accessing and participating in post-secondary education. The findings of the study indicated that the research participants faced barriers which prevented them from advancing their education. They required the three supports offered by WEC-SWP: financial, academic, and personal counselling to access and graduate with a degree in Social Work. Aftergraduation, the participants benefited personally by developing self-confidence, self-esteem, respect, pride, and a healthy, holistic lifestyle. Professionally, they have access to careers rather than jobs which allows freedom, independence, creativity, and satisfaction. A degree provided a full time position and an adequate income to sustain a comfortable lifestyle. These participants are positive role models and change agents within their communities. (Abstract shortened by UMI.)
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".