A Systematic Methods Review of Photovoice Research with Indigenous Young People
Bibliographic record
Abstract
Photovoice is an emerging qualitative research method used to engage community members in research that highlights their lived experiences and initiate change. Photovoice offers potential benefits to research conducted by and with Indigenous communities through privileging Indigenous knowledge and perspectives. There is a lack of synthesized evidence about the usage, benefits, and challenges of conducting Photovoice research by and with Indigenous communities, which this systematic methods review aims to address. We specifically focus on Indigenous young people in Canada, Australia, Aotearoa New Zealand, and the United States. Five databases were searched systematically for articles including keywords for ‘Indigenous’ and ‘Photovoice’. Empirical studies and methods papers reporting the use of Photovoice with majority cohorts of young Indigenous participants were included. Relevant data were extracted and Photovoice methods analysed using an integrative approach. Database searches yielded 1402 articles, with 109 reviewed in full and 41 included in the review. These articles represented 37 unique studies, with most from Canada ( n = 17), and the United States ( n = 14). Our analysis revealed great variability in how Photovoice has been applied across studies with Indigenous young people. However, some notable commonalities include recruitment of participants via community networks, and participant involvement in data collection and analysis. The potential benefits associated with using Photovoice with Indigenous young people included: fostering participant autonomy and authority; photography being familiar and fun; the visual medium being culturally appropriate for Indigenous peoples; and the method being effective for engaging the whole community. Challenges associated with Photovoice included: engagement difficulties between researchers and participants; issues with photography; and ethical complexities. These findings suggest that Photovoice is an appropriate and largely effective method to engage young Indigenous people in research. However, there are logistical and ethical issues associated with the method that require careful consideration.
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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 | 0.031 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.032 | 0.028 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".