Bibliographic record
Abstract
As ‘empowerment’ and ‘agency’ have received wider usage within development research and policy, ambiguities and variant meanings have proliferated. Amidst this conceptual drift, there has also been a tendency to assimilate the two concepts. This tendency is problematic in a number of ways. First, ‘agency’ has various meanings, and the weakest of these captures little of the concept of empowerment. Second, empowerment has a conceptual link with well-being that agency cannot have. Third, when empowerment is assimilated with expanded agency, that agency is not considered in a relational way: the focus is on how the agency of a group or individual becomes greater than it was, not on the degree to which their agency is dependent on or dominated by the agency of others. If ‘empowerment’ no longer refers to social relations, it loses its direct relevance to the transformation of those relations and, as some critics have claimed, it ceases to be a ‘transformative’ concept. After showing that there are cases of empowerment that cannot be captured by conceptions of empowerment that ‘take power out’, I draw upon the capability approach to propose relational conceptions of agency and empowerment that ‘bring power back in’.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.067 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".