What To Do With Settler Stories?
Bibliographic record
Abstract
Working from a critical settler perspective, this dissertation makes several interventions in colonial storytelling in and about Hawaiʻi through contrapuntal readings of texts across media and genre by settler authors or by US corporate media makers. In performing these readings I attend to the fantastic and its multi-genre stories of wonder as a strategy for making visible the settler colonial fantasies in literature of Hawaiʻi by settler authors as well as in corporate action detective and action sf television. These readings are undertaken with hopes of generating resistant knowledge about the structures of belief that shape the identities and relationships to bodies and ancestors of settlers in Hawaiʻi, with an eye toward shifting and ultimately transforming settler relationships to ʻāina. I also consider texts by Kanaka Maoli and Pacific Islander authors that challenge settler colonial fantasies and build possibilities for imagining Indigenous futures and forms of relationship outside of settler colonial storytelling structures.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.047 |
| Scholarly communication | 0.022 | 0.032 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".