Bibliographic record
Abstract
chaotic character, Canadian training policy was theoretically guided or informed – partly by the dominant macroeconomic paradigm, neo-liberalism; and partly by the dominant theoretical paradigm within labour market studies, human capital theory (McBride, 1998). In Canada the conjunction of these two influences produced the deregulation and privatisation of training (and arguably the dilution of training quality), and the devolution of authority over training from the federal government to the provinces (creating, among other things, a patchwork effect and varying standards across the country). In this formulation, privatisation should be understood in two senses. First, training providers would increasingly be private institutions rather than public ones. Second, the cost of training would increasingly be borne by those held by neo-liberal versions of human capital theory to benefit from it – the individuals receiving training and the firms for whom they worked. The overarching tendency, though not always clearly articulated in public policy statements, was towards the mark tisation of training and, in particular, the creation of a training market.2 In political science and political economy, Canada and Australia are frequently taken as
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 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".