Appendix to Chapter 10, "Participation (In)equalities: A Portrait of Canadians’ Political Participation," in "The Working Class and Politics in Canada"
Bibliographic record
Abstract
This document is an appendix to Chapter 10 ("Participation (In)equalities: A Portrait of Canadians’ Political Participation" by Valerie-Anne Mahéo and Marie Fester), which appears in The Working Class and Politics in Canada, edited by Jacob Robbins-Kanter, Royce Koop, and Daniel Troup. About the book: Working-class Canadians are often overlooked by politicians, policy-makers, and political scientists. However, the working class accounts for a substantial share of Canada’s population, and class differences have enduring relevance for how people relate to politics. The Working Class and Politics in Canada argues that changing labour-market patterns, shifting electoral alignments, and increased socio-economic inequality make it essential to revisit the political importance of class. The contributors to this essential volume re-examine the experience of workers in Canadian politics and society, considering the relationship between the working class and political science, political parties, voting patterns, and democratic engagement. How do class status and other aspects of identity – such as region, language, and gender – determine voting behaviour? What happens to working-class representation when the country’s political institutions primarily reflect the priorities of affluent constituents? Drawing on new data and original insights, The Working Class and Politics in Canada offers an up-to-date and much-needed assessment of class and its place in contemporary Canadian politics.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.235 | 0.040 |
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".