Bibliographic record
Abstract
Contents * About the Contributors * Introduction * Program Evaluation and Family Violence Research * Overviews of Research on Family Violence Interventions * How Evaluation Research Can Help Reform and Improve the Child Welfare System * Assessing Family Violence Interventions: Linking Programs to Research-Based Strategies * Research Synthesis in Family Violence: The Art of Reviewing Research * Experimental Designs and Alternatives * What Are the Lessons of the Police Arrest Studies? * Linking Research to Practice: Challenges and Opportunities * Outcomes Research * Treatment Research in Child Maltreatment: Clinical and Research Directions * Canadian Child Welfare Outcomes Indicator Matrix: An Ecological Approach to Tracking Service Outcomes * Evaluating Interventions in Specific Institutional Settings * Evaluating Interventions for Children Exposed to Family Violence * Strategies for Evaluating Dating Violence Prevention Programs * Collaboration and Activist Issues * Community Collaboration to Develop Research Programs in Partner Violence * Ethical Issues in Evaluating Interventions * Human Subject Issues in Batterer Program Evaluation * Index * Reference Notes Included
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.109 | 0.199 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.053 | 0.004 |
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".