Advancing the Measurement of Collective Community Capacity and the Evaluation of Community Capacity‐Building Models
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
Abstract Although more communities, practitioners, and policymakers are recognizing the value of community capacity‐building initiatives, more valid, reliable, and pragmatic measures of collective community capacity are needed to evaluate the effectiveness of such efforts. Over the past 6 years, there has been significant work to advance the measurement and evaluation of collective community capacity‐building initiatives. Accomplishments include the design, testing, and implementation of the Adverse Childhood Experiences (ACEs) and Resilience Collective Community Capacity (ARC3) Survey; the adaptation of the ARC3 Survey for a broader range of community capacity‐building initiatives such as the Collective Community Capacity (C3) Survey; and testing of the C3 Survey in over thirty communities in the United States, Canada, and United Kingdom. These advances will produce more valid, reliable, and pragmatic measures and community capacity‐building models that will contribute to the theory and practice of community‐level change. This chapter highlights work completed over 6 years to develop and test a valid and reliable measure of collective community capacity.
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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 | 0.046 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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