Listening to Writing: Performativity in Strategies Developed by Learning from Indigenous Yukon Discourse, 1968–84
Bibliographic record
Abstract
The central two stories about anthropologist Julie Cruikshank and community-worker-turned-consultant John Hoyt tell of culturally “Western” people, who are chosen by Native peoples in the Yukon Territory to work on the writing of political stories during the period from 1968 to 1984. This historical period, coming only eight years after Native peoples had been declared “persons,” required a rethinking of the communicative and performative strategies previously assumed by non-Native interlocutors. Each writer had to learn to listen differently, generating in their writing not the concepts of the other at the heart of assumptive logics in the anthropological and Western political discourse of the time, but alterior and not-said values that live alongside what Peter Kulchyski calls a “certain kind of writing that is the state.” Each writer does this differently, addressing in Cruikshank’s case the collaborative work of alongside values emerging into socio-cultural discourse, and in Hoyt’s case the collaborative work of setting alongside values in a context that claims value within state politics. Learning about listening to alterior lives is a key skill that has to be relearned by each generation not as predictive strategies but as ways of becoming and ways of knowing.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.049 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".