Lessons in Failing Well: Building Hyper-Migration—a postcolonial, digital, feminist game with refugee youth in Toronto
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
“Hyper-Migration” is an experimental collaborative project with refugee youth in Toronto that investigates how storytelling might be employed in a digital platform to meet the needs of this community, addressing issues such as displacement, social marginalisation and a lack of access to educational and job opportunities. This paper reviews our process of elaborating, vetting and instituting a method combining praxis and participatory-action research, informed by feminist, postcolonial, trauma and refugee studies. In an experimental art-based approach that aspires to design failure (Halberstam), the project shifts in strategy and objective as the refugee youth iteratively test and redesign a social action game. This paper explores this process and how critical theory and in-situ game play worked as techniques, driving a focus on local problems and needs, ultimately establishing analogue practices that took on affordances normally ascribed to the digital. As well, the project demonstrates the deep critical abilities of refugee youth to drive critical game design addressing their concerns, and to target key structural, policy and social issues affecting refugee communities that require social change.
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 | 0.002 | 0.007 |
| 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 | 0.001 |
| 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