The challenges of mapping complex indigenous spatiality: from abstract space to dwelling space
Bibliographic record
Abstract
Participatory mapping has become an indispensable tool in the struggle of indigenous peoples to claim their rights to land and resources. It has also, however, come under criticism for its potential to increase state regulation, replace indigenous conceptions of territory and property, and to create conflict. This paper starts from the premise that the problem is not mapping per se, but the conception of abstract space we allow to frame and guide our representation of indigenous territories, resource use and management. The development of a more effective participatory mapping practice thus requires a critical engagement with the conception of space that participatory mappers are attempting to map. Using research conducted in two Karen communities in Thailand, this paper develops a conception of `dwelling space' meant to better capture the complex spatiality of indigenous resource use and serve as a potential alternative to abstract space. I conclude by arguing for a renewed practice of community-based mapping that takes seriously the spatial complexity of indigenous territory.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".