The Impact of Federalism and Historical Institutionalism on Evangelical Anti-Abortion Mobilization in the United States and Canada
Bibliographic record
Abstract
Diverging paths of evangelical anti-abortion mobilization in the United States and Canada reveal how federal structures and political institutions shape social movement success. While evangelicals in both nations share similar opposition to abortion, their political influence differs dramatically due to contrasting federal systems and party structures. In the U.S., decentralized federalism and a permeable political system enabled evangelicals to build cohesive national networks, align with the Republican Party, and significantly influence abortion policy, evidenced by state-level restrictions and the party’s adoption of anti-abortion platforms. Canada’s fragmented federalism, by contrast, fostered regional and denominational divisions among evangelicals, while its centralized party system marginalized moral traditionalists, leaving anti-abortion efforts fragmented and ineffective. Historical institutionalism further explains these outcomes: The U.S. system’s openness to interest groups allowed evangelicals to exploit electoral and legislative opportunities, whereas Canada’s conflict-averse, executive-dominated polity stifled such mobilization. These institutional differences underscore why abortion remains a defining partisan issue in the U.S. but a peripheral concern in Canada, despite shared ideological foundations among evangelicals.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".