Vocational Education and Training: Discourse, Systems, and Practices of VET in Rural Tasmania and Nova Scotia.
Bibliographic record
Abstract
In this article we offer a comparative analysis of vocational education and training (VET) in two rural regional locations by situating the pragmatic problem of advising rural students against the backdrop of differently structured market-oriented vocational education systems in Canada and Australia, respectively. Each of these jurisdictions offers a particular vision of the place of VET in the context of compulsory education. In rural/regional Canada and Australia, we argue, the socio-material situation within which students live can provide what Bourdieu called “coherent and convenient” educational choices for students to challenge educators to create the conditions for an engaging and non-binary (academic-vocational) approach to compulsory schooling. We conclude, given the constantly changing nature of contemporary occupational opportunities and labour markets, that the goals of the new vocationalism will only be achieved in ruralareas through challenging programming that focuses on capabilities, change, and multiple integrated literacies that span and expand the academic-vocational binary.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".