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Record W7036224325

Benefits of providing supports for non-traditional students to access and complete post-secondary education

2000· other· en· W7036224325 on OpenAlexvenueaboutno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2000
Typeother
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Position (finance)Higher educationDegree programGraduate students
DOInot available

Abstract

fetched live from OpenAlex

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.)

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.177
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2000
Admission routes2
Has abstractyes

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