Using the eye of the camera to bare racism: A photovoice project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Researchers have well established that visible minorities experience discrimination in the labour market and racism at work; however, few studies have explored the experiences of immigrant visible minority women, especially those residing outside of large urban areas. The focus of this article is to explore participants’ experiences of discrimination and racism using photovoice methodology.METHODS: This Canadian study used an arts-based qualitative method in the form of a modified photovoice where 17 participants took photographs of their work and health experiences and discussed the meaning of their photographs and narratives in the interviews.FINDINGS: Results indicate that participants experienced discrimination in the labour market, and racism at work. In the absence of language, participants found the eye of the camera as an effective methodological tool to uncover and communicate their lived experiences of discrimination and racism.CONCLUSIONS: Social workers can utilise photovoice for exploring sensitive issues such as experiences of discrimination and racism in a safe context with marginalised populations. They prevent discrimination and racism in their communities.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it