An exploratory study on the use of Photovoice as a method for approaching FASD prevention in the Northwest Territories
Bibliographic record
Abstract
The Brightening Our Home Fires (BOHF) Project was a project that took place in four communities in the Northwest Territories (NT) from 2011-2012. The purpose of this project was to explore the issue of Fetal Alcohol Spectrum Disorder (FASD) prevention as a health concern in the NT, and to develop an approach that was meaningful for women participants. The intent of the project was to develop a culturally-responsive intervention study addressing links between trauma, and FASD prevention from a social determinant of women’s health perspective through a Participatory Action Research framework. While the project was intended to explore and inform on the topic of FASD prevention work, the primary research question was: What does health and healing look like for you in your community? Thirty women from four communities participated in this project: Yellowknife, Lutsel ‘ke, Behchokö, and Ulukhaktok. This research had differing impacts on participants but an overarching construct was that participation in Photovoice supported women to see their lives in new ways and to reflect upon different struggles and possibilities. Engaging in this research was intended to build relationships, develop community based research partnerships and intended to develop a framework for informing services and practice responses, or enhancements to current service delivery frameworks around FASD prevention and related health concerns.
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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".