Sweeping as a site of temporal brokerage: Linking town and forest in Mozambique
Bibliographic record
Abstract
Building on 18 months of ethnographic research between 2007 and 2011 in Mozambique, this article explores how sweeping practices elaborate multiple temporalities and thus can serve as powerful sites of “brokerage” where diverse actors and their many agendas meet. Sweeping renders daily activities legible to local residents and illegible to others. Daily sweeping just outside of the home signifies a day’s routine beginning and a family’s availability for receiving visitors. Sweeping also prevents the rapidly growing miombo woodland undergrowth from invading the home space, which partly explains differences in why many local residents see the woodlands as advancing and environmentalists’ argue that the “forest” is disappearing due to illegal logging. Limited understandings of sweeping as banal or wasted time miss the links between many urban-based non-governmental organization and activist practitioners who implement their projects in rural areas. Sweeping blurs and challenges assumed boundaries between urban and rural woodland spaces.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".