“The possibilities of an Indigenist anti-colonial research praxis: a response to ‘the false promise of decolonial research: the complexities and limitations of Decolonizing methods and methodologies” by Leon Moosavi
Bibliographic record
Abstract
Decolonial scholarship is not a panacea to coloniality, but it can be a site of counter-hegemonic possibility. While acknowledging the historical and contemporary ways in which colonial scholarship has been framed, controlled, and disseminated by the dominant and has been used to pathologize and subjugate the colonized ‘Other’, decolonial scholarship offers the opportunity to name and challenge Eurocentric epistemicide. This paper seeks to reflect on and engage in a dialogue with the principles, possibilities and limitations included in Leon Moosavi’s article, ‘The False Promise of Decolonial Research: The Complexities and Limitations of Decolonizing Methods and Methodologies,’ and offer additional de/anti-colonial considerations for this framework. This paper will also examine the extent to which Moosavi’s decolonial research framework allows for the critique of dominant research epistemologies, offers the space for the colonized to locate ourselves and acknowledge our own complicities in dominant imperialist and colonialist scholarship methods, allows the space for researching back and promoting remembrance, relationality, resistance, reciprocity, recovery, and a path to decolonization.
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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 | 0.082 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.093 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.009 | 0.025 |
| 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 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".