Where does Canada's social science research data live? An evaluation of data disposition
Bibliographic record
Abstract
This paper will bring together information from different sources to evaluate the current disposition of Canadian social science and related research data. It will review the more than 20 repositories hosting Canadian social data. Sources of information about Canadian data include the Re3data international data registry and National Research Council Canada Gateway to Research Data, the Canadian Association of Research Libraries Portage project and the Fairsharing data directory, Canadian open government resources, and commercial resources like data.mendeley.com add substantial additional information about Canadian social sciences research data. This review will document the subjects covered, and organizational connections between repositories and the consortia efforts working to coordinate Canadian data collecting. The paper will compare social science repositories to the larger body of data repositories. It will compare government provided data sources, academic, institutional, subject based shared consortia data sources, and publisher based collection data approaches. The paper will outline the considerable progress which is being made in data collection. It will also delineate major issues still to be addressed. Though Canada's data landscape is particular to Canada its course of development and problems will be instructive for other countries developing data services and resources.
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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 | 0.018 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".