North American indigenous curators’ constructions of indigenous knowledge
Bibliographic record
Abstract
This dissertation aims to show how indigenous curators working in museums and universities across the United States and Canada construct indigenous knowledge as a discursive object and thus influence the production and circulation of indigenous knowledge in North American societies. The study is framed through the Sociology of Knowledge Approach to Discourse (SKAD), which accommodates meaning-making and material dimensions of discourses. Qualitative and interpretive research methods are employed including semi-structured in-depth interviews with indigenous curators, analysis of textual documents (scholarly work by indigenous curators and museum mission statements), and analysis of multimodal documents (an exhibition with indigenous content), in order to capture and describe actualizations of discourses of indigenous knowledge by indigenous curators. Indigenous knowledge is constructed discursively as injured knowledge (“invisible” through “erasure” of spatial and temporal presence). Indigenous curators position themselves as the social actors authorized to articulate this status endogenously and to address it by making a case for the compelling (spatial and temporal) presence of indigenous knowledge. In this respect, they employ topographical and chronographic vocabularies to articulate threats to indigenous knowledge and to propose model practices by means of which these threats may be addressed. There are roles associated with indigenous knowledge stewardship, which the curators fulfill, more or less innovatively, by interacting with other actors, by engaging in discursive and model practices, and by using affordances of the material practices of indigenous knowledge. The dissertation contributes to the literature in Library and Information Science by looking at the constructed nature of cultural knowledge. It makes visible the creative work of indigenous curators as a group of information professionals who remain unstudied despite the important work they do in serving the information needs of both aboriginal communities and the larger society.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.034 | 0.025 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 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".