<i>La Frontera: Forests and Ecological Conflict in Chile's Frontier Territory</i>, by Thomas Miller Klubock
Bibliographic record
Abstract
La Frontera: Forests and Ecological Conflict in Chile's Frontier Territory, by Thomas Miller Klubock. Durham & London, Duke University Press, 2014. ix, 385 pp. $27.95 US (paper). Thomas Klubock has written an excellent book based upon exhaustive research that pieces together the social and environmental effects caused by large scale transformations to forests during a sustained period of nation-building and state development in southern Chile. He provides a chronological narrative, one that seeks to locate the origins of today's miracle in complex and contested relationships that began at least a century ago. Klubock explains how forestry development remade the social landscape and how campesinos confronted changing environmental conditions. The setting involves an extensive southern region known colloquially as La Frontera, stretching between the Bio Bio and Tolten rivers and from the Andes to the Pacific. Klubock begins after the military defeat of the last independent Mapuche groups as the weak state reduced these groups into commonly held and circumscribed settlements. Although European immigration proved paltry, enormous land concessions in this frontier allowed for wheat production to expand alongside livestock rearing and the first conservation reserves. Forestry laws facilitated modern forestry production and secured estate owners' property rights at the expense of prior rural residents. The system shepherded by the state limited land fraud and unchecked forest clearing, which had social consequences, in particular, violent peasant protests against the enclosure of the lands they used for their livelihoods. Klubock's investigation shines in his dramatic analysis and close reading of the Ranquil rebellion, an organized uprising against the largest estate families that exposed the ways campesinos' relationships to the state were also tied to ecological processes. The 1930s and 1940s brought an abrupt shift away from failed attempts to create a breadbasket in the south. Instead, Monterrey pine plantations became the proposed solution to diminished yields and infertile soil. Seen as a way to restore value to increasingly barren lands and combat rampant erosion, pine also promised to link the rural sector to industrial changes. Swapping wheat for pine had major restructuring effects based upon state driven incentives and rewards. By reorganizing land and labour relations, planting pine provided a way to present the state and large landowners as modern and productive. It will come as no surprise that rather than resolve these festering issues, tree plantations created new tensions of their own as they swallowed up peasant lands and depleted rural unionization. By the 1960s, this spiral of degradation and deepening rural poverty created pressures for agrarian reforms. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".