Bibliographic record
Abstract
From the Second World War until recently, the Canadian government saw providing training -including the sponsorship of training -to the labour force as one of its roles. 1 Since 1996, in the current neoliberal environment, all that has changed.It is now basically up to the individual to Wnd and pay for her/his own training.2 Even during the period in which the government provided training, women's access to it was not equal to that of men.For example, in the early period much of the training was to prepare soldiers returning from the Second World War for re-entry into the labour force.However, from the 1960s to the 1990s, equity did become an issue in labour force training, and some programs that targeted women and other equity groups were offered.Although equality was not achieved, some progress was made.Beginning in the 1980s another group, this one comprised of social assistance recipients (SARs), was targeted for sponsorship in training programs.In fact, this was an overlapping group since most of the SARs were women.Then, in the late 1980s, women-only programs were dropped in favour of a gender-neutral approach -much to the dismay of women's organizations and programs.By 1996, with the changes in the Employment Insurance (EI) program, all equity initiatives seem to have disappeared.In the new programs, such as Skills, Loans and Grants, participants have to meet Employment Insurance eligibility criteria even in order to receive loans.Women are given no special consideration and, in fact, at least in New Brunswick, are under-represented and, in some cases, grossly under-represented among the participants.3 Training has always been an area of federal jurisdiction.However, in 1996 a process of devolution began; that is, the delivery of training was transferred from the federal government to the provincial governments.The timing of the changes brought about by devolution coincided quite closely with the changes in the Employment Insurance program, and hence the two sets of changes are very much inter-related.On 13 December
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".