What characteristics account for who participates in adult basic education at Vancouver Island University? A case study of policy and practice
Bibliographic record
Abstract
This study is an in-depth examination of what accounted for participation in Adult Basic Education (ABE) at Vancouver Island University (VIU) from 1995 to 2015. I use a qualitative case study and discourse analysis to investigate participation in relation to how policies, perceptions, and contexts influence understandings of participation in ABE at VIU. I consider what other scholars have said about participation in ABE, particularly in regard to barriers to participation and student motivation. In particular, I draw on ideas presented in studies done by Rubenson and Desjardins (2009) and Boeren (2011) on how participation in adult education is impacted by power and governmentality located in welfare regimes and their associated policy structures. I take this idea a bit further by studying one institution in depth to learn that power and governmentality are present at macro, meso and micro levels. I then focus on how governance structures shape understanding and control who participates at the local level. In this way, I fill a gap in current literature on participation in adult education by explaining how various actors make meaning of policy in their local context and how these same meanings contribute to finding alternative solutions to longstanding participation problems.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".