Bibliographic record
Abstract
Harpoon of the Hunter,originally written in Inuktitut syllabics and published serially in 1969/70, is frequently characterized as the “first Inuit novel” ( McGrath 1984 , 81; Chartier 2011 ). It was deemed the “breakthrough” ( McNeill 1975 , 117) eagerly awaited by those whose stated goal was to save Canada’s traditional northern culture and its stories, songs, poems and legends from being swept aside by the onslaught of southern modernity. Markoosie’s text helpfully allows discussion of (post)colonial contact zones constructed in and through translational acts such as self-translation, retranslation, and relay/indirect translation as these intersect with Indigenous literature. This article explores the complex trajectory, involving various stakeholders, of the translation, circulation and reception of this important contribution to not only Inuit literature, but Canadian literature as a whole. It examines some relevant features of the author’s own translation of his text into English (1970) and traces them through the two existing French translations by Claire Martin (Markoosie, tr. Martin 1971) and Catherine Ego (Markoosie, tr. Ego 2011).
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.035 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".