Learning from <em>The Lived Experiences of Aging Immigrants</em>: Extending the Reach of Photovoice Using World Caf&eacute; Methods
Bibliographic record
Abstract
This article reports on a series of Stakeholder Outreach Forums hosted in Canadian communities from 2018 to 2019. These forums built on a previous research project, The Lived Experiences of Aging Immigrants, which sought to amplify the voices of older immigrants through Photovoice and life course narratives analyzed through an intersectional life course perspective. The forums used World Café methods to encourage cumulative discussions among a broad range of stakeholders who work with or influence the lives of immigrant older adults. Participants viewed the previously created Lived Experiences of Aging Immigrants Photovoice exhibit, which provided a springboard for these discussions. The forums’ aim was to increase the stakeholders’ awareness of the experiences of immigrants in Canada as they age and to create space for the stakeholders to reflect upon and discuss the experiences of aging immigrants. Here we illustrate how the forums complement the narrative Photovoice research methodology and highlight the potential of Photovoice and targeted outreach strategies to extend academic research findings to relevant stakeholders. Across all forums, participants identified structural and systemic barriers that shape experiences of and responses to social exclusion in the daily lives of immigrant older adults. They further identified challenges and strengths in their own work specific to the issues of social inclusion, caregiving, housing, and transportation. Intersectoral solutions are needed to address the structural and systemic roots of exclusion at the public policy and organizational levels.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".