Not so far away: a collaborative model of engaging refugee youth in the outreach of their digital stories
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
A majority of literature on participatory visual methodologies focuses on the creation stage of a project, but less is written about involving participants in the outreach phase. Drawing on the experience of collaborating with three refugee youth on a city‐wide school tour of their digital stories, this article explores the benefits and challenges of extending participatory processes beyond process and into outreach. ‘On Tour’ was the last phase of Mapping Memories, a five‐year Montreal‐based participatory media project with refugee youth. Through ten media workshops, the project reached out to over 150 youth, and offered them the chance to learn new media skills, reflect on their past experiences, work in collaborative contexts, strengthen their networks and express themselves creatively as they shaped their experiences into compelling digital stories, photo‐essays, mixed media collages, and even bus and walking tours. ‘On Tour’ was developed in the last year of the project to explore the impact of combining live presentations with digital stories to instigate peer‐to‐peer dialogue about stereotypes that frame refugees as victims, outsiders or ‘burdens to the system’. The outreach initiative permitted us to explore ethical and critical pedagogical frameworks when bringing digital stories into classrooms. We also had a chance to confront our assumptions regarding youth involvement in outreach and to explore the following questions: What ethical considerations need to be taken into account when bringing youth participants and their sensitive digital stories beyond process and into the realm of outreach? And what methods should be used to ensure that everyone involved benefits?
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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