A bout of time: decolonization and futurity in Indigenous speculative fiction
Bibliographic record
Abstract
Works of Indigenous speculative fiction (SF) depict a perspective of temporality that differs from the mainstream Western conception of time as linear and teleological. Novels such as Cherie Dimaline’s The Marrow Thieves and Hunting by Stars and Waubgeshig Rice’s Moon of the Crusted Snow portray settler colonialism as an ongoing process rather than a historical event; in doing so, they challenge hegemonic notions of settler futurity by asserting an Indigenous presence and affirming the inevitability of Indigenous futures. This thesis analyzes Dimaline’s and Rice’s works to examine how Indigenous SF reorients readers into Indigenous temporalities and critiques assumptions of Indigenous disappearance or victimry through their portrayals of settler colonial violence and environmental destabilization. These authors use apocalyptic and dystopian settings to demonstrate how Indigenous peoples will survive the end of colonial capitalism through self-determination and a reliance on their own epistemes. Both the characters in and readers of Indigenous SF are motivated to generate Indigenous futurisms from within the present through a revitalization of Indigenous languages and practices. This critical examination of Indigenous SF situates the genre within the contexts of ecocriticism, decolonization (or biskaabiiyang), and futurity to showcase how different perceptions of time alter the possibilities for the future.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.035 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".