Native Peoples and Knowledge Organization: Perspective from the Indigenous Subject Representation to Promote Latin American Approaches
Bibliographic record
Abstract
The situation of many indigenous cultures in Australia, North, Central, and South America can be described as one of marginalization or minorization. Subject representation of Indigenous knowledge constitutes one of the contemporary crossroads since, through it, the predominant mentalities of classificationists, classifiers, and indexers are revealed, and this can consolidate hegemonic visions or propose appropriate alternatives to the cultural particularities of Indigenous peoples. From a critical perspective, this work aims to contribute to the systematization of the growing literature on indigenous warrant in KO. The methodology offers quantitative and qualitative data as results of the application of six categories of analysis. The most significant scientific production on the Indigenous issue in KO has come from Canada, the United States, and Australia since 1971. In Latin America, publications only began in 2023, particularly in Brazil. We identified two possible paths to improve the subject representation of the area: adaptation of pre-existing schemes or the creation of new knowledge organization systems specialized in Indigenous culture. Cultural hospitality and indigenous warrant are two relevant tools to guide solutions to improve the subject representation of native cultures. Among other conclusions, from the KO, progress was made in the hierarchy of indigenous knowledge, and there was a need for these cultures to impose their ways of categorizing, naming, and relating things. The urgency of promoting academic production on the subject in Latin America is highlighted, considering the historical and contemporary dimension of its great indigenous civilizations throughout its territory.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".