Bibliographic record
Abstract
mahikan ka onot collects the finest work of accomplished Indigenous poet Duncan Mercredi, from his first book in 1991 to recent unpublished poems. These are poems of life on the land as well as life in the city, vibrant with the rhythms of traditional Cree and Métis storytelling but also with the clamour and the music of the streets. This book brings the work of Duncan Mercredi (Cree/Métis) back into the public eye, providing a new generation of readers with the opportunity to experience his unique artistry. Mercredi brings to these poems the sensibility of a Cree speaker and a renowned oral storyteller, revealing a deep attachment to the land and a nuanced understanding of the complexities of contemporary Indigenous life. In startlingly direct, plainspoken language, the poet explores themes of cultural resurgence and steadfast connections among the generations, even amid the unfolding tragedies wrought by colonialism. Some of these poems are memories of traditional life on the land, especially in the time before Manitoba Hydro radically altered Mercredi’s home community of Grand Rapids, Manitoba. Others focus on the urban Indigenous experience, based upon Mercredi’s longstanding and intimate knowledge of Winnipeg. Like mahikan, the wolf, Mercredi’s characters are often outsiders in certain contexts, but the poems reveal other perspectives that allow us to understand their loyalty and their love of community. The volume includes an afterword by Duncan Mercredi and an introduction by Métis scholar Warren Cariou, both of which provide resources for deeper study of the poems.
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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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.017 |
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".