Common Approach to Impact Measurement: Four Community-Driven Flexible Standards for More Interoperable Impact Data
Bibliographic record
Abstract
Common Approach to Impact Measurement (Common Approach) is a set of four flexible impact measurement standards designed to empower charities, nonprofits, coops, social purpose businesses (collectively referred to as social purpose organizations or SPOs), and those they serve to identify which impacts are most meaningful. These standards are not designed to make measurement more rigorous or more accurate; rather, they make measurement more useful and interoperable, and, eventually, more attuned to the priorities of those impacted.
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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 | 0.182 | 0.361 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.031 | 0.032 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.031 | 0.026 |
| Open science | 0.014 | 0.031 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".