How Game Changers Catalyzed, Disrupted, and Incentivized Social Innovation: Three Historical Cases of Nature Conservation, Assimilation, and Women’s Rights
Bibliographic record
Abstract
We explore the impact of “game changers” on the dynamics of innovation over time in three problem domains, that of wilderness protection, women’s rights, and assimilation of indigenous children in Canada. Taking a specifically historical and cross-scale approach, we look at one social innovation in each problem domain. We explore the origins and history of the development of the National Parks in the USA, the legalization of contraception in the USA and Canada, and the residential school system in Canada. Based on a comparison of these cases, we identify three kinds of game changers, those that catalyze social innovation, which we define as “seminal,” those that disrupt the continuity of social innovation, which we label exogenous shocks, and those that provide opportunities for novel combinations and recombinations, which we label as endogamous game changers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".