Decolonization in Focus: A Bibliometric Analysis of Scientific Articles from 2010 to 2023
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Decolonization refers to the process of undoing or dismantling the systems and ideologies imposed during colonialism. Recognition of colonialism's enduring impacts has increased scholarly attention to conceptualizing and advancing decolonization. Methods: A systematic literature review approach was employed to analyze existing research on decolonization from 2010 to 2023. Quantitative bibliometric methods were used to extract metrics from publications and perform statistical analyses of trends. The Scopus database provided coverage of different four subjects. Results: A total of 980 documents were analyzed from 636 sources. Key findings include steady annual increases in production, with outputs doubling from 2019 to 2020. The United States, United Kingdom, Canada and South Africa contributed the most publications. "Decolonization", "colonialism" and population-centric keywords dominated. Conclusion: Decolonization remains an important topic of interdisciplinary and global research. Future work will be conducted on a comprehensive bibliometric analysis in this field. Novelty: This study applied bibliometric techniques to provide valuable information about quantifiable trends, relationships and gaps within the extensive body of decolonization. Network and clustering analyses revealed collaborative patterns and thematic developments over time.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.095 | 0.192 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it