Between metis and techne: politics, possibilities and limits of improvisation
Bibliographic record
Abstract
Geographers, especially those working in developing country contexts have often encountered improvisation because it plays a critical social and cultural role. Engaging with anthropologist James Scott’s conceptualisation of metis – contextual, practical and flexible skills and knowledge – and techne – universal technical knowledge – this paper furthers the geographical scholarship on the politics of improvisation.The paper makes three main contributions. First, using metis and techne, it provides a new conceptual repertoire for making sense of improvisation. The paper places improvisation at the nexus of metis and techne. Second, it pushes the understanding of the morality of improvisation by attending to the role of relationships of power in morally and materially legitimising improvisations. Third, although states and experts celebrate and actively engage with improvisation, this paper demonstrates that they also create limits and boundaries for improvisation. These limits demonstrate a contradiction in experts’ actions.This paper is based on a nine months ethnographic research on two energy projects carried out in 2012–13 in five villages in Bihar, an eastern state of India. It used participant observations, home tours, interviews and group discussions.
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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 | 0.026 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.133 |
| Scholarly communication | 0.029 | 0.024 |
| Open science | 0.002 | 0.028 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".