Bibliographic record
Abstract
Over the last decade and a half, socio-cultural geographies have witnessed a genuine explosion of interest in the ethnographic tradition. Such interest is due in part to the increasing acceptance of non-representational ideas across the field and the way these ideas have constructively informed the long-standing debate on the analytics, esthetics, and politics of ethnographic representation. Non-representational theoretical ideas have influenced the way ethnographers tackle important methodological and conceptual undercurrents in their work, such as vitality, performativity, corporeality, sensuality, and mobility. This article aims to capture a few of the characteristics of this constantly evolving non-representational ethnographic style. Non-representational ethnography seeks to cultivate an affinity for the analysis of events, practices, assemblages, structures of feeling, and the backgrounds of everyday life against which relations unfold in their myriad potentials. Non-representational ethnography emphasizes the fleeting, viscous, lively, embodied, material, more-than-human, precognitive, non-discursive dimensions of spatially and temporally complex lifeworlds.
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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 | 0.048 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".