Bibliographic record
Abstract
In this chapter I explore the constructive value of informal relationality and everyday ethics for nuancing the conversation on ethics in community-based refugee research projects. This chapter reflects on the case of “Worn Words,” a digital storytelling and research co-creation project that I carried out in Vancouver, Canada, which aims to interrupt narratives that objectify refugees as abject subjects or problems to be solved by enacting everyday research ethics and the principles of cultural refugee studies in media production. Working with migrant communities as knowledge holders, rather than “objects” of inquiry, Worn Words offers a critique of refugee discourse and raises a potentially transformational question: “to whom is our research responsible?” Here, the question of how informal relationships are operating is important if we are to avoid extractive tendencies in representational media and art production. I discuss how “maintaining relational integrity” in the absence of a formal partnership agreement with community organizations enabled a process that prioritized grassroots innovation with under-resourced refugee sector organizations and interests of community members without pressure from powerful funders and formal institutional mandates.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".