Towards a More Collaborative Political Science: A Partnership Approach
Bibliographic record
Abstract
Abstract The research model that has dominated the discipline of political science in Canada is based on a top-down approach that defines and finds solutions to problems as researchers see them, and diminishes the real world concerns of social and political actors. Advocating a more collaborative political science, we argue for a partnership approach that engages those actors in the research process, including problem definition, research design, analysis and knowledge dissemination. This inclusion sharpens the focus of the research and produces more contextually valid and socially valuable knowledge. We draw upon our research experience working with Indigenous communities in Canada to illustrate the value of this approach, and carry out a review of partnership-based research published in The Canadian Journal of Political Science. We find little evidence of partnership-based research in our flagship journal and discuss the implications for the future of our field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".