Toward decolonizing sustainability research: a systematic process to guide critical reflections
Bibliographic record
Abstract
With growing attention to the ethical and equity implications of Western-based approaches to research, the urgency of decolonizing research has emerged as a critical topic across academic disciplines, including the field of sustainability. The complexity and messiness of this endeavour, however, may translate into uncertainty among researchers about how and where to start. This is partly due to a lack of guidance, training, and accountability mechanisms through Western academic institutions. In this paper, we advance a three-step process that systematically guides critical reflection toward respectful engagement of local and Indigenous communities, as well as other marginalized groups, by drawing on the literature and on learnings from a recent graduate student-led initiative. The process we develop aims to provide a pragmatic starting point for decolonizing research and a counterpoint to conventional modes of research. Such a process will not only foster accountability, respect, and reciprocity but also movement toward locally relevant, context-appropriate, and action-oriented research outcomes. Our three-step process also challenges Western-based and extractive research practices and seeks to facilitate a shift in mindset about the purpose of research and how to approach it.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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".