The Evolution of Collective Strategies among Organizations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many organizations are made up of other organizations that have decided to act collectively as with research and development consortia, industrial alliances, trade associations, and formal political coalitions. These collective organizations can be characterized by their differing strategies: some are general in scope, while others specialize on a more narrow purpose. What explains the prevalence of generalism and specialism among collective organizations? We develop an ecological model in which collective organizations compete over member organizations. Assuming that an organization joins a collective when its objectives match that of the collective, our model predicts a generalism bias in the ecology of founding and growth among collective organizations. This outcome is predicted to be path dependent, however, emerging over time according to relatively minor differences in initial conditions. These predictions are supported in an analysis of founding and growth rates among US R&D consortia, and the model helps to account for the numbers, sizes, and strategic diversity of these consortia.
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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 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it