Bibliographic record
Abstract
Pasquet, Jacques and Marion Arbona. My Wounded Island. Translated by Sophie B. Watson. Orca Books, 2017.Imarvaluk lives on a small island called Sarichef on the Chukchi Sea coast of Alaska. Imarvaluk tells the story of how her people live on their island, in their town of Shishmaref. She explains how they used to live in igloos but now live in small wooden homes. The men in her family still hunt bearded seal, walrus, elk, and caribou as their ancestors did. In the summers the family moves to a camp on the mainland by the Serpentine River where they hunt caribou, catch fish, and pick berries.Imarvaluk also tells of how their lives are changing because of the sea, and the monster within it. During winters long ago, the sea would freeze and protect the island from the waves. The ice would also enable her family to hunt. The creature in the sea has caused winter to retreat earlier and earlier, making the pack ice unstable to hunt on, and it slowly swallows the island into the sea. Imarvaluk describes how the home of her people will eventually disappear and how they may have to relocate to Nome, when her island becomes uninhabitable. Through her relationship with her grandfather, Imarvaluk explains how the culture of her people is very much at risk as they face the end of their island.This beautiful and emotionally packed story is remarkable in its ability to convey how environmental impacts are being felt by this Inupiat community. Illustrations by Marion Arbona use paint and texture to convey impactful images of life on Shishmaref, weaving the monster of the changing environment together with Inupiat mythology. It was refreshing to read a children’s book that takes up the very real changes caused by climate change, and in so doing, does not hesitate to leave the ending unresolved. This being said, My Wounded Island could evoke strong emotions and may be better read with an adult, so that there can be discussion about the issues it presents. This doesn’t mean parents should shy away from this book as it is truly a beautiful and impactful read for both young and old.Highly recommended: 4 out of 4 stars Reviewer: Hanne PearceHanne Pearce has worked at the University of Alberta Libraries since 2004. She holds a BA and MLIS and is currently working towards her Master of Arts in Communications and Technology. Her research interests include: visual communication, digital literacy, information literacy and the intersections between communication work and information work. She is also a freelance photographer and graphic designer.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.090 | 0.048 |
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".