An examination of three key factors: Alcohol, trauma and child welfare: Fetal Alcohol Spectrum Disorder and the Northwest Territories of Canada
Bibliographic record
Abstract
This article was generated from the research project “Brightening Our Home Fires” (BOHF), a Photovoice project on woman’s health and wellness that took place in the Northwest Territories (NT) from 2010-2012. This research was funded by the First Nations and Inuit Health Branch (FNIHB) of Canada. Approximately 30 women from four different communities in the NT participated in this project; Behchokö, Ulukhaktok, Yellowknife and Lutsel 'ke. The method utilized in this study was Photovoice, a Participatory Action Research (PAR) model that is identified as a qualitative research approach. While the research project was a Fetal Alcohol Spectrum Disorder (FASD) prevention project, the broader focus was on issues related to health and healing within a northern context in the NT from the perspective of northern women, and within the construct of health. The primary focus of this article is the presentation of a model that was generated from a review of the research literature gaining a deeper understanding of broader social concerns in the NT. Three key factors are highlighted as critical in developing a deeper understanding of the context of women’s health issues that are important to consider in FASD prevention work: 1) trauma, 2) alcohol abuse and 3) child welfare involvement and the impact on communities in the northern territories of Canada as it presently exists in the NT. This research served to provide a broad perspective of social problems that may be mitigating factors in the presentation of FASD in a northern context.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".