‘Concepts have teeth’: capacities and transfers in the digital modelling of Blackfoot material culture
Bibliographic record
Abstract
Remarking on the way that colonial encounters produced complex entangled networks between indigenous communities and Euro-Americans, the Mohawk anthropologist Audra Simpson (2007, 69) writes that ‘concepts have teeth and teeth that bite through time’.She is writing about the differential power of one account over another in establishing the terms of being seen or being present.This paper explores the way in which these kinds of concepts and encounters produce certain kinds of affective capacities. This paper introduces an archaeology-art project concerned with digitally modelling Blackfoot material culture in UK museum collections, using photogrammetry and Reflectance Transformation Imaging (RTI). Blackfoot sacred artefacts, such as medicine bundles, are involved in a series of complex exchanges and transfers (Lokensgard 2010). In this paper we argue that the transfer and exchange of medicine bundles offers a paradigm for thinking about material encounters. What capacities are revealed by the various exchanges involved in the project? The project is based on a series of exchanges: between academics and members of an indigenous community; between Canadian and UK institutions; between Universities and museums; and between academic disciplines and their associated practices and techniques.How do the series of encounters involved in these exchanges make a difference to the outcomes and trajectories of the project; how do capacities emerge and extend through the networks established and created by the project? References Lokensgard, K.H. 2010 Blackfoot religion and the consequences of cultural commoditization. London: Routledge. Simpson, A. 2007 On Ethnographic Refusal: Indigeneity, ‘Voice’and Colonial Citizenship, Junctures 9, 67-80.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".