Bibliographic record
Abstract
In 2000, I published Distant Relations: How My Ancestors Colonized North America, a non-fiction exploration of my own family’s involvement in North American colonialism from the 1600s to the present. This personal essay reflects on the context, genesis, process, and consequences of writing this book during a decade of intense ferment in Indigenous–settler relations in Canada amid the revelations of horrific abuse at residential schools and the discovery that my highly respected grandfather had been involved with one. Considering the book from the perspective of 2021, I consider the strengths and limitations of this kind of critical family history and the degree to which public discourses and academic discussion of Canada’s history and settler complicity in colonialism have changed since the book was published. Arguing that critical reflection on family history is still an essential part of unlearning colonial attitudes and recognizing the systemic and structural ways that colonial disparities and processes are embedded in settler societies, I share a critical family history assignment that has been an essential and transformative pedagogical element in my university teaching for both Indigenous and non-Indigenous students.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.053 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".