“I Thought We Had No Rights” – Challenges in Listening, Storytelling, and Representation of LGBT Refugees
Bibliographic record
Abstract
Storytelling serves as a vital resource for Lesbian, Gay, Bisexual and Trans* (LGBT) refugees’ access to asylum. It is through telling their personal stories to the Canadian Immigration and Refugee Board that LGBT refugees’ claims for asylum are accessed and granted. Storytelling also serves as a mechanism for LGBT refugees to speak about social injustice within and outside of Canada. In this article, I explore the challenges of storytelling and social justice as an activist and scholar. I focus on three contexts where justice and injustice interplay in LGBT refugee storytelling: the Canadian Immigration and Refugee Board, public advocacy around anti-queer violence and refugee rights, and oral history research. I describe how in each arena storytelling can be a powerful tool of justice for LGBT refugees to validate their truths and bring their voices to the forefront in confronting state and public violence. I investigate how these areas can also inflict their own injustices on LGBT refugees by silencing their voices and reproducing power hierarchies.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.038 | 0.045 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| 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".