On the politics of speculative fiction: A conversation with Drew Hayden Taylor
Bibliographic record
Abstract
The alternate realities and imagined futures of speculative fiction provide a rich source of material through which to interrogate our views of history, elucidate our contemporary cultural milieu and chart what we see as possible. This article attends to the politics of Indigenous–Settler relations through an engagement with speculative fiction. Spatially and temporally located in the country now called Canada in the twenty-first century, the work centres on a conversation between the author, a Settler Canadian, and writer, playwright and humourist, Drew Hayden Taylor, from the Curve Lake First Nation. A full transcript of the conversation, edited for length and clarity, is provided. In it, Taylor describes his speculative writing practice and engagement with Indigenous futures. The article concludes with the author’s reflection on the process of decolonization, situating engagement in Indigenous futurisms as a step in this process.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.040 | 0.039 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 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".