Bibliographic record
Abstract
When I began thinking about this project on democratic disengagement among young Canadians, I might have been considered part of that demographic group on a generous definition of the term.By any reckoning, that is no longer the case, which is a roundabout way of saying that the project has been a fair time in the making, from initial conception through to publication of this volume.Along the way, I have received generous support and encouragement from a number of individuals and organizations.My engagement with debates about Canadian democracy began when I was serving as research director of the Governance Program at the Institute for Research on Public Policy (IRPP) from 1998 to 2001.Colleagues at the IRPP, including its then president, Hugh Segal, as well as academic collaborators Richard Johnston, André Blais, and many others, were enthusiastic supporters of, and contributors to, the Strengthening Canadian Democracy project initiated during my tenure.The interest kindled at the IRPP carried over to the University of New Brunswick, where the current project gradually took shape.Several seminar classes, at both the undergraduate and graduate level, on the theme of democratic disengagement have provided a valuable opportunity to discuss key ideas with members of the age cohort that constitutes the focal point of the study.Helping to move the project along at different stages were several bright and industrious research assistants: Vincent French, who, among other assignments, had the task of gathering datasets and conducting preliminary analysis for the comparative research presented in Chapter 3; Julie Kusiek, who carried out background research on various themes related to adolescence underpinning the analysis of Chapter 9; and Shane DeMerchant, who came to the project in its latter stages and provided assistance in tying up loose ends throughout.The study makes extensive use of survey data to investigate relevant patterns of democratic engagement.The head of the Government Documents, Data and Maps department at the University of New Brunswick library, Elizabeth Hamilton, provided initial advice in locating relevant datasets, as
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.400 | 0.215 |
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; the direct Gemma label and the distilled Codex classifier 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".