Bibliographic record
Abstract
So many relations and relationships have sustained me during this journey.When I began researching the solidarity encounter, I was living in Tkaronto (Toronto), the traditional territory of several Indigenous nations, including the Mississaugas of the Credit, Anishinaabe, Chippewa, Haudenosaunee, and Wendat peoples.Currently, I live, love, and work in St. John's on the island of Ktaqmkuk (Newfoundland), translated from L'nui'simk as "far across place." Ktaqmkuk is the ancestral homelands of the Beothuk and the traditional territory of the Ktaqamkukewe'k Mi'kmaq, including the Qalipu and Miawpukek First Nations.I would also like to recognize the Inuit of Nunatsiavut and NunatuKavut and the Innu of Nitassinan, and their ancestors, as the original people of Labrador.I ofer these land acknowledgments as part of my ongoing commitment to non-colonizing solidarity and decolonizing settler colonialism in the nation-state known as Canada.Tis research would simply not have been possible without the participants: those who chose to be identifed by their real names, Zainab Amadahy (Cherokee, Seminole), Ruth Green (Kanien'kehá:ka), Lee Maracle (Stó:lō/Métis), Rebeka Tabobondung (Anishinaabe) and Wanda Whitebird (Mi'kmaq); and the nineteen other women who remain anonymous.Tank you for trusting me with your knowledge.A big shout-out to my friends and comrades in struggle at No More Silence past and present, including Audrey, Barbara, Carmen, Cass,
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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.377 | 0.246 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".