Bibliographic record
Abstract
Abstract The purpose of this chapter is to revisit and expand upon the concept of response-ability, shifting from the deconstructive homework of previous chapters to working towardsareconstructive response which renders science education more hospitable towards Indigenous science to-come. Braiding in the work of Torres Strait Islander scholar Martin Nakata’s theorizing of the cultural interface, which accounts for the ways in which hybridity between ways-of-knowing-in-being are unequal, problematic, and yet rife with possibility, this response takes the form of re(con)figuring scientific literacy. In four movements, this response: a) identifies scientific literacy as a central yet uncertain concept whose critical inhabitation is ripe for other meanings and enactments; b) explores Karen Barad’s subversion of scientific literacy as agential literacy as a productive location to rework the connectivity towards IWLN and TEK; c), utilizes agential literacy as proximal (yet differing) relation to bring in Gregory Cajete’s conception of Indigenous science as ecologies of relationships; and d) explores the generative points of resonance between agential literacy and ecologies of relationships. The chapter concludes with a cautionary note on points of convergence and points of divergence, wherein the proximal relation between agential literacy and ecologies of relationships is productively troubled.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.029 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".