A Relationship Focused Approach to Epistemic Injustice in Global Development Theory and Practice
Bibliographic record
Abstract
Miranda Fricker's theory of epistemic injustice articulates the connections between ethics and epistemology that come to light in the harms caused when someone is wronged in their capacities as a knower. Although Fricker's account has provided an important contribution to the academic literature, its many flaws mean that a new approach to epistemic injustice is needed. This new account will focus more on structures of society, context, and relationships to better understand how epistemic injustices happen. This new approach will then be applied to the broad context of global development, and to the specific case study of Cuba's education and health care policies. The goal of this project is to show that epistemic injustice interferes with effective and ethical global development work aimed at improving the well-being of people, and how taking a more structural, contextual, and relational approach will mitigate the harms of epistemic injustice.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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; a candidate call from one teacher head, 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".