Bibliographic record
Abstract
In 2004, settler scholar Emanuelle Dufour became aware of a “silence” with regard to residential schools and ongoing colonialism, systemic racism, inadequate curricular material in schools, and sought to find answers by meeting with community members, Elders, spokespeople, students, professionals, families, and many others. Dufour is an artist at heart, and the product of her findings became a “carnet de rencontres,” a notebook of coming-togethers, in which her fifty+ interlocutors are rendered “speaking,” quite literally, on and within the pages, while advocating for the importance of Indigenous cultural security within the education system. Their presence is undeniable, and their voices carry the narrative. Originally published as C'est le Québec qui est né dans mon pays!, this translation creates a bridge, from one colonial language to another, that will enable conversations across and beyond spaces and languages. It aims to shed light on colonial mainstream narratives in Canada and, more precisely, in Québec, by considering the politics of linguistic hegemony and the double exiguity that Indigenous peoples often find themselves in, calling for a better understanding of how the province’s specific colonial history has had a profound and continued impact on its 11 Indigenous Nations. This book’s unusual (academically-speaking) form as a “carnet”, or diary, becomes an anthology of statements of witnessing, which, coupled with the illustrative narrative, bears its decolonizing mission. Quebec Was Born in My Country! ultimately is about foregrounding common and collective experiences, with the crucial goal of furthering education.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.002 |
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".