A Relationship Focused Approach to Epistemic Injustice in Global Development Theory and Practice
Bibliographic record
Abstract
MirandaFricker'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 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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".