2001 Pan-Canadian Education Research Agenda Symposium Teacher Education/Educator Training: Current Trends and Future Directions
Bibliographic record
Abstract
This paper will focus on human resource issues associated with the demand, supply and retention of teachers in the Canadian province of Newfoundland and Labrador. The results will help determine whether or not a sufficient labour pool exists to meet the province's demand for educators and will provide valuable labour market information for young people considering a career in the education sector. As well, the paper will be valuable for government policy makers and educational leaders concerned about the quantity and quality of the labour supply. If used wisely, the results will help to ensure that all schools, regardless of the social and economic circumstances of their particular communities, are able to attract highly qualified teachers. 1 Teacher supply and demand: An analysis of current developments in Newfoundland and Labrador Changes in the teacher labour market brought on by demographic changes, the recent trend towards globalization of the workforce and policy changes introduced by provincial governments have converged to stimulate a debate about whether or not there exists a general teacher shortage in the province of Newfoundland. Based on a more extensive study reported elsewhere (Dibbon and Sheppard, 2001), this paper will argue there is not an overall teacher shortage in the province of Newfoundland, at this time. However, there is evidence to show that there is a high demand for teachers in the rural and remote areas of the province and that there is a high degree of variation in the demand for teachers from one area of specialization to another. As such, the paper will investigate the forces that are converging to influence teacher supply and demand in Newfoundland and Labrador, specific measures of teacher demand and the sources of teacher supply.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.019 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".