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Record W7064467254

Canadian mega-mining in Central Mexico: Ecologically Unequal Exchange, Violence and Organized resistance 1992-2016

2017· other· en· W7064467254 on OpenAlexaboutno aff

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2017
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersUniversidad Nacional Autónoma de México
KeywordsMilitarizationResistance (ecology)Political ecologyOpposition (politics)SustainabilityPoliticsInequalityParticipant observationSocial movement
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines the historical dynamics of ecologically unequal exchange, coloniality of power, and systemic violence embedded in mining activities. With the use of a combined Marxist and De-colonial critical approach, it accomplishes a political ecology analysis of Canadian mega-mining in central Mexico and the socioenvironmental conflicts related to it, particularly in Cerro de San Pedro and the sacred territory of Wirikuta, between 1992-2016. In like manner, the research focuses on how the discourses and promises of development, economic growth and sustainability have been used to conceal processes of accumulation by dispossession, often accompanied by systemic violence and militarization that aim to de-articulate opposition and resistance movements in contexts of exacerbated poverty, social inequality and environmental degradation. The present study was carried out through fieldwork, participant observation and in- depth interviews in Central Mexico during December 2010, December 2011 and February-March 2017.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0110.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.008
GPT teacher head0.218
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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