Bibliographic record
Abstract
Due to the limitations of existing archival theories and methodologies, there are few clear options that allow underrepresented and marginalized communities to represent themselves ethically, faithfully, and responsibly in their own voices in mainstream archival institutions. As a result, many of these communities lack knowledge and fundamental pedagogical resources about themselves and their history in Canada. Based on research from the author’s one-year master’s degree, this article uses a critical ethnographic framework and oral history interviews to understand the archival needs of a segment of the Afghan diaspora that has long been settled in Canada. The Afghan Canadian participants agreed that digital archives could provide a solution to the community’s dearth of knowledge and material about itself – its own histories and stories. The research demonstrates that a critical ethnographic framework can be applied as an instrument in the archives in order to understand the desires, identity-formation processes, and representations of a marginalized community to ensure faithful archival representation.
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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 | 0.050 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".