A man and his island: The island mirror in Michael Crummey’s Sweetland
Bibliographic record
Abstract
Between 1946 and 1975, dozens of islands and outports in the Canadian province of Newfoundland and Labrador were abandoned as part of a government resettlement policy. Families and communities were torn apart, and a culture and way of life that revolved around the fishery changed irrevocably. The practice, which continues to this day, has been well documented, particularly by artists and writers. Michael Crummey’s 2014 novel Sweetland is a recent iteration. The relationship between humans and place is complex: on an island, with compressed space and a very real boundary that is the ocean, emotional attachments to one’s place are often heightened and distilled. What happens when a person is displaced from his or her island; when bonds of attachment are severed and one’s mirrored double is destroyed? Sweetland offers a fictional lens through which we see an example of a mirrored relationship between an island protagonist and his island setting. Exploring themes of attachment to place, and what Barry Lopez calls a “storied” or “reciprocal” relationship with the land, this paper examines what happens to a man when confronted with leaving an island he knows as deeply as his own body and soul; and how the island reacts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.022 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".