The impact of inter-actor competition on administrative burdens: theorizing “consequent populations” using the illustrative case of gamete donation governance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Research on administrative burdens has highlighted how policy design and implementation shape citizens’ experiences of the state. Little attention has been paid to how conflicts between target populations can also generate administrative burdens. Using the case of gamete donation policies in Canada, this article argues that target populations can shape administrative burdens for one another through competition within policy arenas, with winners experiencing less costly policy implementation at the expense of other target populations. In doing so, it positions citizens as agents who both experience and produce the costs of policy implementation. To capture these dynamics, the article introduces the concept of consequent populations to identify distinct groups disadvantaged by the outcomes of target group competition, and consequent costs to specify the sub-category of administrative burden borne by this group.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it