Promoting family wellness and preventing child maltreatment : fundamentals for thinking and action
Bibliographic record
Abstract
Based on extensive research over many years, with a broad range of participants in Canada and internationally, this collection of essays is an important contribution to the child welfare agenda. It deals with the promotion of emotional well-being in families, and the prevention of child maltreatment. Values, policies and resources are examined as both facilitators of, and barriers to, effective action. The authors interviewed nearly 150 people, including researchers, policy makers, social workers and clients of the child welfare system. Both theoretical and practical issues emerge, as the authors discuss the social context of abuse and the scientific context wherein policy is made. They conclude that the following social conditions are essential in effectively reducing abuse: upheld values of self-determination and the health of children; sufficient material and psychological resources for children and families; family-friendly parental leave and child support policies, and empirically grounded and tested prevention programs. Contained within the work is extensive examination of current issues in Aboriginal child welfare. The authors advocate certain collective approaches to child-raising, inspired by current and historical Aboriginal practices. Promoting Family Wellness is of relevance to all those involved in child welfare, and to researchers and students too. It is readable and clear enough to be of interest to the general reader who is interested in this intellectually complex and emotionally fraught topic.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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".