Bibliographic record
Abstract
We begin with an obvious observation about trafficking in alternatives-when one engages with the possibility of better worlds as an anthropologist or as a sociolegal scholar, this entails engaging with social analysis, both how analysts parse the world and how their fieldwork interlocutors do.Analyzing crafting the otherwise involves tracking one's fieldwork interlocutors' own reflexive social analysis, analyses which shape the strategies deployed, and the responses these strategies elicit.This focus on reflexivity appeals to anthropologists and sociolegal scholars because it allows us to turn away from the conceptual traps inherent to hegemony and resistance.Scholars are encouraged to explore the techniques people use to imaginatively try new forms, instead of focusing largely on whether a set of practices recreates state or institutional power or resists it (Coutin & Yngvesson, 2023, de la Cadena, 2018, Gibson-Graham, 2002, Graeber, 2009).Sometimes fashioning the otherwise involves balancing two alternative framings of relations at the same time (Coutin & Yngvesson, 2023), sometimes it involves imagining alternative ways of inhabiting already existing social structures using available repertoires in new ways (Gibson-Graham, 2002).Quite frequently, analysts interested in the otherwise ask how their fieldwork interlocutors fashion new social orders that can function alongside the social orders already present.Crafting the otherwise thus depends on a rela-
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.049 |
| Scholarly communication | 0.016 | 0.024 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".