How time matters in the UN Human Rights Council’s Universal Periodic Review: Humans, objects, and time creation
Bibliographic record
Abstract
Abstract The Universal Periodic Review (UPR) of the United Nations Human Rights Council is an innovative monitoring mechanism in the international human rights law system. As the UPR matures, scholars have increasingly sought to stand back and understand it as a process. In this article, I take work in this vein further by considering more closely the actors involved in the UPR – humans and objects – and highlighting the time creating effects that emerge from the relationships between them. Across the various stages of the UPR, a range of temporalities – from cyclicality and linearity to retrogression and suspension of time – are produced and sustained by people, reports, data, lists, microphones, screens, computers, action plans, and desks, just to name a few. I argue from this that time is materially made in the review process, often in micro and taken for granted ways. In its operation, the UPR appears as a collection of temporal assemblages. Or, in language drawn from actor-network theory (ANT), an assortment of fluid and interweaving sets of actants networked together who generate ideas of time across its practice. Apprehending time creation in this material, the ANT-inflected way is highly significant for scholars and practitioners interested in the UPR. It holds potential to influence how this process can be understood, approached, and located within international human rights law as itself a larger, time creating actor-network.
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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 | 0.108 | 0.210 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.035 | 0.016 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.008 | 0.005 |
| 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".