Community sidelined: The loss of community focus in differential response
Bibliographic record
Abstract
Abstract Differential response (DR) first emerged as one component of a child welfare paradigm that emphasized the need to engage communities in supporting families and children. However, the role of community in differential response has received little attention in recent literature. We examine the intellectual history of these ideas, tracing changes in the framing of community engagement in relation to DR over time. We find that attention to community has been sidelined by an increasingly narrow definition of DR that focuses on the existence of an alternative approach to engaging with screened in families, rather than the building of community support networks. There is currently no clear and explicit theoretical framework connecting community engagement to DR. We find that the absence of such a framework has given rise to a series of conceptual debates about the definition and purpose of DR. The development of a literature that elucidates the topic of community engagement in DR may serve to resolve some of these debates.
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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 | 0.025 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".