Bibliographic record
Abstract
Indigeneity has been a site of relationally produced knowledge deemed scientific and political. In this article, I offer an experimental description of Miskâsowin—an Ininiw/Cree theory of science, technology, and society. This methodological piece is part of an overall project that seeks to understand how changes in technoscience often correlate with changes in the relationships and biotechnologies that colonial nation-states and their citizenries, scientific fields and their researchers, and bioeconomies and their consumers use to form themselves through, in spite of, and (sometimes) as Indigenous peoples. Creating Indigenous theories of the technosciences that affect them is disruptive of colonial ontologies of knowledge and sovereignty. Miskâsowin is part of an emergent subfield of Indigenous Studies: Indigenous Science, Technology, and Society (I-STS). I use this framework to map partial connections whereby Cree concepts of tapwewin (truth-telling), miskâsowin (finding one’s core), and misewa (all that exists) resonate with relational academic theoretical frameworks including that of Pierre Bourdieu, Michel Foucault, and Aileen Moreton-Robinson. I do so in ways that are uniquely adapted to my (the researcher’s) relationships (and the genealogies that they are routed through) with genomic knowledge and indigeneity; with the scientific and policy fields in Canada (and beyond); and with my own research/er integrity.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.052 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".