Library services and indigenous peoples in Latin America: Reviewing concepts, gathering experiences
Bibliographic record
Abstract
There have been library services for indigenous peoples in Latin America since at least the 1980s; they are small-scale, very specific experiences that, until recent times, have been poorly systematized and scarcely discussed. Throughout their brief but intense history – a story that has been replicated in many other countries around the world, from Canada to New Zealand – these services have faced a series of crossroads, contradictions and conflicts that they have not always been able to resolve, from the controversial label ‘indigenous libraries’ to their scope and the categories and methodologies they use. From a first-person perspective (the author was among the first library and information science professionals to work with this topic in Latin America and has been active in the field for the last 20 years), this article briefly reviews the state of affairs in South America, pointing out the main milestones in the history of these services in the region. It identifies some concepts and ideas that require urgent discussion from both a library and information science and interdisciplinary framework, and suggests some paths to explore in the near future.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".