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Record W4294705235 · doi:10.1017/9781009110693.006

Rehabilitating Guerillas in Neo-Extractivist Guatemala

2022· book-chapter· en· W4294705235 on OpenAlexaff
Karine Vanthuyne, Marie-Christine Dugal

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsTestimonialOpposition (politics)FaithDemocracyPoliticsPolitical scienceCriminologyState (computer science)Armed conflictHistorySociologyLaw

Abstract

fetched live from OpenAlex

During Guatemala’s internal armed conflict (1960–1996), most local leaders in San Miguel Ixtahuacán, San Marcos, were “disappeared.” When, between 1995 and 1998, the church-led Recovery of Historical Memory Project (REHMI) was collecting testimonies from victims of the armed conflict, no one agreed to speak up. It is only since 2014, in the midst of growing local opposition to large-scale mining, that relatives of the “disappeared” have begun to narrate their experiences as victims of violence. In this chapter, I will examine how the recent “recovery” of historical memories of the brutal repression of local activism did not defeat but instead revitalized radical hope for a “just Guatemala” and in the process produced new conceptualizations of victimization and perpetration. How has public truth-telling contributed to this peculiar form of engagement? Despite a brutally crushed revolution, a failed democratic transition, and growing state-level corruption, anti-mining activists in San Miguel maintain faith in regaining the control of their lands and lives through their involvement in testimonial practices, formal politics, and legal action.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.006
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.178
Teacher spread0.164 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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