Ethics and Action Research in Emancipation-Based Endeavours: Projects of Heart or Projects of Publication?
Bibliographic record
Abstract
University standards for attaining tenure-track positions, tenure, advancement of rank, and successful periodic evaluation in universities in the Global North primarily center on attainment of research grants and publications. This article considers the ethical implications of these values when action research projects are carried out with impoverished communities in the Global South. Simultaneously, when impoverished communities in the Global South work with Global North universities, they often do so with the experiences of universities and other foreign organizations (religious charities, non-government-organizations, not-for-profits, etc.) having timeframes and funding allocations set to standards of the usual two to five years, along with the knowledge that the “foreign-researcher” will, more than likely, be transient in their lives. Understandably, this relationship of competing needs and dedication will shift moralities of the impoverished community and “local-researcher” given the growing understanding that the foreign-researcher’s commitment is often tied to institutionally required outputs that give them little benefit. This article uses reflexivity to expose the often-challenging experiences of three Action Researchers in different situations as they work on a liberation, emancipation and social-justice based project focusing on Education, Health and Development in a rural region of central Malawi.
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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 | 0.132 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.218 |
| Scholarly communication | 0.026 | 0.021 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".