1 Franchising Social Change: Logics of Expansion Among National Social Movement Organizations with Local Chapters
Bibliographic record
Abstract
National social movement organizations with widely dispersed local affiliates have been common since the turn of the 20th Century. And, they have continued to proliferate in recent years. At the turn of the 21st Century approximately one quarter of local U.S. SMOs were affiliates of national ones. Yet little scholarly attention has been directed at describing their common structural forms, the demography of those forms, or the contrasting organizational logics that lead their founders and leaders to prefer one structural template over another. The recent emphasis upon professionalized national SMOs has diverted attention from an exploration of the role that local affiliates of national franchise SMOs play in facilitating individual activism. This paper makes national SMO franchises and their affiliates the substantive focus and is motivated by an attempt to describe and explain the evolution of the population of national SMO franchises. After putting national franchises into context of the potential variety of SMO forms, I proceed to establish their prevalence of local affiliates among local SMOs with members. Then a number of key dimensions of SMO franchise structure are explored (a commonly recognized name and symbol,
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".