Establishing the content validity of the community safety and peace index
Bibliographic record
Abstract
There is a relative paucity of research on the drivers, indicators and mediating mechanisms underlying community level safety and peace promotion. We developed community-level safety and peace indicators drawing on two community-based studies. Guided by the values and principles of Community Based Participatory Research (CBPR) and classical test methodology, the initial index development phases included: conceptualisation, identification of dimensions, operationalisation of dimensions, refinement of indicators, item generation, and item reduction phase. Content validity evidence is crucial for developing scientifically sound instruments and demonstrating a clear causal connection between the targeted construct and the items designed to measure it. The aim of this study is to establish the content validity of the Community Safety and Peace Index (CSPI), which primarily drew on local community-based knowledges in its development. The different data sets were triangulated in a retrospective evaluation workshop, three expert panel reviews, community input, and test developers' consensus. The team reached consensus on the conceptualisation and measurement of community safety and peace, operationalisation of key constructs, identification of dimensions, indicators, and questionnaire items.
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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 | 0.028 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".