Preferences of Residents in Four Northern Alberta Communities Regarding Local Post-Secondary Programming
Bibliographic record
Abstract
The western Canadian province of Alberta has used some of the proceeds from exploitation of its extraordinary natural resources to make available a range of post-secondary training and education opportunities to residents. While these provisions appear comprehensive, this study examined how well they actually suit the express needs of the residents of remote, Northern areas of the province, many of them Aboriginal. 
 
 The literature shows that while Aboriginal people are underrepresented in Canada in university enrollments, they are no longer underrepresented in college or other institutions, suggesting that gains have been made for some residents of rural and remote parts of Canada. Further, when Northern residents (especially Aboriginal males) complete advanced training, Statistics Canada reports they are highly successful in employment and income. Access is the pivotal issue, however: leaving the local community to attend training programs elsewhere is often disruptive and unsuccessful. As will be seen, the issue of access arose in this study’s findings with direct implications for distance delivery and support.
 
 This study was conducted as part of Athabasca University’s Learning Communities Project (LCP), which sought information about the views and experiences of a broad range of northern Alberta residents concerning their present post-secondary training and education opportunities. The study addresses an acknowledged gap in such information in relation to Canada in comparison with other OECD countries.
 
 Results are based on input from 165 individuals, obtained through written surveys (some completed by the researchers in face-to-face exchanges with the respondents), interviews, discussions, and observations, conducted with full-time or part-time residents of the study communities during 2007 and 2008. The four northern Alberta communities studied were Wabasca, Fox Lake, Ft. McKay (sometimes MacKay), and Ft. Chipewyan, totaling just over 6,000 residents.
 
 While respondents had varied backgrounds in relation to training and education, consensus emerged on several points: training in the studied communities must be flexible to be realistic; the negative emotional and economic impacts on families and individuals when they are forced to leave the local community to take training can be enormous; alternatives such as distance education may now be acceptable to and technologically feasible for many; and certain subjects (especially business-related courses, pre-employment preparation, such as safety and computer skills, trades training, and basic skills upgrading programs in essential skills such as math, English, writing, and life skills) were of broad interest to these residents. 
 
 The LCP was cautioned that future programming inspired by this research should avoid mistakes made by others in relation to northern learners and their local realities: not considering students’ preferences for programming; employing inappropriate technologies; failing to provide adequate orientation and support to the learning system; and failure to use existing, proven delivery models.
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How this classification was reachedexpand
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 | 0.007 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".