Bibliographic record
Abstract
Rural Alberta is decreasing in population with a resulting reduction in services to the people who continue to live outside the metropolitan areas of Calgary and Edmonton. As services within rural communities decline, a commensurate increase in stress occurs for the population that remains. By delivering a program that matches post-secondary students with non-profit/voluntary sector (NPVS) organizations that are in need of skilled workers, Volunteer Alberta, through its sponsorship of the Serving Communities Internship Program (SCiP), struck upon a plan to provide for rural re-development. Volunteer Alberta worked through Alberta's 21 post-secondary institutions to promote internships that were available throughout the province. During the 2011/12 school year volunteer placements occurred. Throughout the fall of 2012 we conducted an evaluation of the program through a study that utilized comprehensive online surveys, as well as interviews with a purposeful sample of interns and NPVS organizations. Survey and interview data revealed that both the interns and the NPVS organizations were highly satisfied with the SCiP format, the services provided to them by Volunteer Alberta, and the quality of the internships, and the interns they acquired. SCiP intern motivation came from the opportunity to use skills and knowledge developed in post-secondary programs in such a way that they could later use the experience as evidence of their ability to future employers. Interview data from both the interns and the NPVS organizations in rural areas of the province revealed that volunteer post-secondary student exposure to rural community organizations led to a positive change in perception about the work of the NPVS in general and rural communities in particular. Evidence of change of perception was strong enough to indicate that a longitudinal study should be conducted to see if the positive perception of rural communities attained through working there will be acted upon, and lead to an increased movement toward paid work in the non-profit/voluntary sector in both urban and rural areas of the province. Keywords: Rural development, youth internships, community development
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".