Bibliographic record
Abstract
In 2022 the Niagara Region welcomes the Canada Games; 2022 also marks the reintroduction of the Indigenous game of lacrosse. By thematizing lacrosse, this book celebrates the role sport plays in promoting cultural diversity. It features work by poet Jason Stefanik / Jay Stafinak, who grew up and lives in a Métis / mixed environment; photographer Marjorie Kaniehtonkie Skidders of the Mohawk Nation at Akwesasne; Franco-Ontarian author Paul Savoie; and the Toronto Experimental Translation Collective (TETC). They invite us to discover lacrosse from a creative perspective. Their talent and their enthusiastic participation to this volume in French and English are a poignant demonstration of kindness and mutual appreciation. The book reflects our diversity. En 2022, la Région du Niagara accueille les Jeux du Canada ; 2022 marque aussi la réintroduction du jeu autochtone de la crosse. Par cette thématique, le présent ouvrage veut célébrer le rôle du sport dans la promotion d’une plus grande diversité culturelle. Il inclut des contributions du poète Jason Stefanik (Jay Stafinak), qui a grandi et vit dans un environnement mixte et métis ; de la photographe Marjorie Kaniehtonkie Skidders de la Nation Mohawk à Akwesasne ; de l’auteur franco-ontarien Paul Savoie ; et du Collectif torontois de traduction expérimentale. Ielles nous invitent à découvrir le jeu de la crosse d’une perspective créative. Leur talent et leur participation enthousiaste à ce volume en français et en anglais nous proposent une généreuse expérience d’appréciation mutuelle. Ce livre reflète notre diversité.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.263 | 0.104 |
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".