Michael Crummey’s River Thieves in the light of rescue history
Bibliographic record
Abstract
Born and raised in Newfoundland and Labrador, Michael Crummey uses his inside knowledge to describe the region's peculiarities in vivid detail.All four of his novels are set in Newfoundland and weave a story of its inhabitants throughout different moments in the island's history.Though Crummey's prose is broadly characterized as historical fiction, his novels differ from their traditional counterparts.This article aims to invite a reading of Crummey's works through the prism of rescue history, a concept recently introduced by a Polish scholar, Ewa Domańska.Rescue history, drawing on frontier and post-colonial studies among others, is preoccupied with local, potential, existential and affirmative history whose goal is to rescue the future.Although the concept of rescue history encompasses a variety of disciplines and activities, this article will focus on the literary realization of the notion of rescue history in Crummey's debut novel River Thieves, published in 2002.Based on historical accounts of Captain David Buchan's expedition to Red Indian Lake, whose aim was to encourage trade and put an end to hostilities between English settlers and Beothuks, the novel encourages a compassionate revisiting of the chronicled events.Weaving an intricate web of human relations and dependencies, Crummey manages to restore agency to those who are situated on the periphery either due to gender, status or origin, thus reminding the reader that we are all capable of changing the course of history.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".