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
My documentaries, I hope, present counter narratives to the dominant imaginative fantasies of Canadian nationalism that refuse to see the colonial histories being played out in the contemporary migrant worker programs. Migrant labor programs are not new concepts. They are engineering the racial make-up of Canada’s citizenry as they always have. The contemporary versions in practice today are extensions of historic labor schemes developed by the Canadian state to designate the “preferred citizen” according to class and race. Canada’s colonial history institutionalized the wholesale genocide of the indigenous peoples of the land. The erasure of the First Nations’ histories and cultures from Canada’s history has been actively resisted by Indigenous communities today, a resistance that challenges the whitewashing of Canada’s roots. It is imperative to remember how deeply entrenched labor and immigration programs were and continue to be in fostering the imaginative fantasy of Canada as white. Canada’s national railways were built in the 1800s by Chinese railroad workers who paid exorbitant fees in the form of head taxes to work in the dangerous sites, laying the train tracks that would eventually literally make national unity feasible.
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 | 0.000 | 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) | 0.013 | 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