Bibliographic record
Abstract
In this paper, we discuss the ways our ongoing collaborative performance(s) of “X: where our paths cross” straddle the varied intimacies of live and virtual spaces of visiting and activate noncolonial concepts of host-guest relations that enact Indigenous sovereignties and confront the certainty of settler emplacement, while considering the responsibilities of settler guesting. This series of virtual, in-person, and hybrid performances brings together Morin’s work with Tahltan knowledge and sovereignties through embodied activations of a publication of Tahltan stories “collected” and transcribed by white anthropologist James Teit in 1919 and 1921 and Decter’s work in disturbing patterns of white settler entitlement and settler-state sovereignty, in part through interrogations of the Group of Seven’s landscape painting traditions, which date to the same period as Teit’s publications. Engaging the X where Indigenous sovereignties intersect with the necessary activation of settler responsibilities across our different ancestries, this work results from an ongoing collaborative relationship between artist-scholars Peter Morin, who is of Tahltan Nation and French Canadian ancestry, and Leah Decter, an Ashkenazi Jewish white settler. Our contribution to this issue blends writing and time-based media in the form of this text, an animated poetic version of a transcript from one of our early exchanges about the project, and video excerpts from two of the fully virtual performances.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.015 | 0.024 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.146 | 0.037 |
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".