Between Freedom and Fear: Children's Views on Home Alone
Bibliographic record
Abstract
Journal Article Between Freedom and Fear: Children's Views on Home Alone Get access Mónica Ruiz-Casares, Mónica Ruiz-Casares Mónica Ruiz-Casares, Ph.D., is a postdoctoral fellow in the Department of Psychiatry and at the Center for Research on Children and Families, McGill University. Her professional interests include the well-being and protection of children without parental supervision cross-culturally, including child-headed households and children home alone, as well as the translation of scientific knowledge for policy making, programme development and evaluation. Cécile Rousseau, MD, is an associate professor of psychiatry at McGill University. Her clinical work is with refugee and immigrant children, and she works in shared care for health institutions and school boards. She has developed and evaluated school-based prevention programmes for immigrant and refugee children using different creative expression modalities: sand play, drawing and storytelling, theatre and video. Correspondence to Mónica Ruiz-Casares, Ph.D., 7085, Hutchinson, Office 204.2.14, Montreal (Quebec), Canada H3N 1Y9. E-mail: monica.ruizcasares@mail.mcgill.ca Search for other works by this author on: Oxford Academic Google Scholar Cécile Rousseau Cécile Rousseau Mónica Ruiz-Casares, Ph.D., is a postdoctoral fellow in the Department of Psychiatry and at the Center for Research on Children and Families, McGill University. Her professional interests include the well-being and protection of children without parental supervision cross-culturally, including child-headed households and children home alone, as well as the translation of scientific knowledge for policy making, programme development and evaluation. Cécile Rousseau, MD, is an associate professor of psychiatry at McGill University. Her clinical work is with refugee and immigrant children, and she works in shared care for health institutions and school boards. She has developed and evaluated school-based prevention programmes for immigrant and refugee children using different creative expression modalities: sand play, drawing and storytelling, theatre and video. Search for other works by this author on: Oxford Academic Google Scholar The British Journal of Social Work, Volume 40, Issue 8, December 2010, Pages 2560–2577, https://doi.org/10.1093/bjsw/bcq067 Published: 30 May 2010 Article history Accepted: 01 April 2010 Published: 30 May 2010
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".