Researcher Education in the Social Sciences: Canadian Perspectives About Research Skill Development
Bibliographic record
Abstract
In the current climate, there is an increasing emphasis on skill development for research candidates across disciplines and across nations. In Canada, postgraduate education programs attempt to influence relevant skills and attitudes through students ’ engagement in coursework, independent research projects (e.g., a student thesis), and research assistant positions where students serve as apprentices and assistants on academic-led research projects. This presentation draws for a set of interviews with academics and postgraduate students to understand how these components of postgraduate education affect students’ development of skills and their self-identities as researchers. The interviews are specifically intended to uncover the ways that academics and postgraduate students perceive and experience researcher education and skill development in social science disciplines at one university. The presentation represents one of few Canadian studies of researcher development at the postgraduate level and provides a good complement to investigations from other nations.
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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 | 0.037 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.070 | 0.053 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.012 |
| 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".