Legal scholarship: an analysis of law professors' research activities in Ontario's English-speaking common law schools
Bibliographic record
Abstract
A current discussion of Canadian higher education reveals the increasing importance of research within the university and in government higher education policy. At the same time the political economy of Canadian higher education has been analyzed in terms of a neo-liberal response to economic globalization. This study contributes to that emerging scholarship by focusing specifically on the political economy and academic legal research. The purpose of this study is to describe the current context of law professor's research activities in terms of subject matter, theory and methods, organization, products and funding in order to ascertain if there have been shifts in this context over the past 20 years. The implications of the findings were critically analyzed in terms of a socio-critical framework that considered the relationship between knowledge and professionalism within the context of the political economy of higher education. This study provides important empirical data on the research activities of full-time tenured or tenure-track law professors in Ontario's English-speaking common law schools. It also identifies areas of change and stability over the last 20 years. The study involved the collection and analysis of data from law professors using survey and interview methodology. Some of the findings are unexpected. They show some evidence of influence on law professors' research activities associated in the higher education literature with neo-liberal restructuring. However, in important ways the research context of law professors does not conform to the university research model. The findings suggest that the law school, rather than becoming marginalized in the new university, has consolidated its position in the university. The findings suggest this is largely because of factors not associated with research, such as the strong teaching mission, the deregulated tuition fees that the professional program attracts, and their proximity to a wealthy and entrepreneurial profession that offers potential endowments and donations. Although legal scholars are facing challenges to, and pressures on, their intellectual work, they still enjoy a strong position in the university, not because of their research activity, but in spite of it.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.017 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".