Attracting, preparing, and retaining under-represented populations in rural and remote Alberta-North communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>For several years, the government of the western Canadian province of Alberta has drafted policies and conducted research on the problem of populations under-represented in adult education. This Alberta-North and Athabasca University study, funded by the Alberta government’s Innovation Fund, uses the advice and educational experiences of northern former and present students, and of other community members, to identify ways of better attracting, preparing, and retaining under-represented populations in northern Alberta communities through provision and training in the use of distance delivery methods.</p><p>The research reported here commences with a review of the literature to investigate the following: 1) the contribution distance education makes globally to learning access in remote areas (and resulting economic growth for under-served populations); 2) how support is provided to retain isolated students; and 3) the help needed to assist remote students to complete distance programs. Community consultations with social service and education agencies in three communities were conducted in order to obtain their perspectives about what helps to attract and support students to educational programs and the barriers students typically encounter, which might be mitigated by distance methods. Finally, a survey was designed and distributed in 87 Alberta-North communities in northern Alberta and across Canada’s Northwest Territories to add perspective to the consultation results.</p>
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it