Reshaping Gender and Class in Rural Spaces, edited by BarbaraPini and BelindaLeach, Burlington, VT: Ashgate, 2011. 246 pp. $114.95 (cloth). ISBN: 978–1‐4094–0291–6.
Bibliographic record
Abstract
What happens when two vastly different, seemingly incommensurable forms of knowledge collide?Andrew Mathews's Instituting Nature deftly answers this question in its topically rich and theoretically complex exploration into the history of the pine forests of Oaxaca, Mexico.Methodologically eclectic, Mathews uses archival work and ethnography, along with his training in forestry, to tell his story.On one side, there was the emerging technical, scientific knowledge of forest "management" held up by the Mexican forest service and logging companies.On the other side was the local indigenous groups' inherited knowledge of swidden and milpa agriculture.Venturing into silviculture, environmental anthropology, and science studies, the book describes the myriad conflicts that have created and continually remade Oaxacan forests over the last century.By examining these conflicts, Mathews draws provocative conclusions on the relationships between states, publics, and knowledge institutions by asserting that the state is a "co-production" between epistemic and political agents.The story of the Oaxacan forests is tied up with the forestry bureaucracy, logging companies, and the indigenous groups that used the forests for fuel and subsistence through charcoal burning and swidden agriculture.After a period of private control before the Mexican Revolution in 1910, scientific forestry moved past the weak Mexican state and into communities and forests during the early twentieth century.Beginning in the early 1940s, the state gave substantial land concessions and logging rights to large commercial and parastatal companies, with the Fabricas Papeleras de Tuxtepec (FAPATUX) paper company being the most prominent in Oaxaca.FAPATUX exploited the indigenous communities as well as the forests, resulting in a powerful community-led backlash against the logging company during the 1970s.The state cancelled the concessions in 1983 and implemented a successful, though at times tenuous, community forestry model that still operates today.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".