A Comprehensive Bibliometric Review of Indigenous Knowledge Research
Bibliographic record
Abstract
This study presents a comprehensive bibliometric review of Indigenous knowledge research from 2000 to 2025, using data retrieved from the Scopus database. Through quantitative mapping with VOSviewer and Bibliometrix, the study examines publication trends, collaboration networks, and thematic developments within the global research landscape. Results reveal three dominant clusters: environmental sustainability and climate resilience; ethnobotany and traditional medicine; and Indigenous health, gender, and social well-being. Australia, Canada, and the United States emerge as leading contributors, while growing participation from Africa, Asia, and Latin America reflects a gradual diversification of epistemic voices. The findings highlight a paradigm shift from descriptive documentation of Indigenous practices to integrative and decolonial research frameworks emphasizing sustainability, equity, and community empowerment. This study contributes to understanding the intellectual evolution of Indigenous knowledge research and provides evidence-based insights for fostering inclusive, cross-cultural collaboration and ethical engagement with Indigenous communities in future scholarship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.048 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".