Bibliographic record
Abstract
The controversial Pascua-Lama mining project, straddling the border between Chile and Argentina and operated by Canada’s Barrick Gold, gained international notoriety when the company proposed to “move” three glaciers located at the mine site. The glaciers variously appeared, changed form, and disappeared as the project was developed, presented to the public, subjected to various modifications, and ultimately put on hold. The environmental impact assessment process created an inventory of the landscape that turned nature into an object of environmental management. At the same time, the element of public participation embedded in Chile’s environmental impact legislation helped to mobilize local and international activism. El polémico proyecto minero de Pascua-Lama que maneja la empresa canadiense Barrick Gold en la frontera entre Chile y Argentina quedó sometido al escrutinio internacional cuando la empresa propuso “mover” tres glaciares situados en la mina. Los glaciares aparecieron, cambiaron de forma y desaparecieron conforme el proyecto se desarrollaba, presentaba ante el público y era sometido a diversas modificaciones; en última instancia, fue suspendido. El proceso de evaluación de impacto ambiental dio lugar a un inventario del paisaje que convirtió a la naturaleza en un objeto de gestión ambiental. Al mismo tiempo, la participación ciudadana fundamentada en la legislación chilena de impacto ambiental ayudó a movilizar activistas locales e internacionales.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".