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Record W2301392366 · doi:10.3138/gsi.10.1.06

State Strength, Non-State Actors, and the Guatemalan Genocide: Comparative Lessons

2016· article· en· W2301392366 on OpenAlex
Frederick M. Shepherd

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenocide Studies International · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideState (computer science)IndigenousContext (archaeology)Political sciencePopulationWeaknessDevelopment economicsEconomic growthCriminologySociologyGeographyLawMedicineEconomicsDemography

Abstract

fetched live from OpenAlex

This article focuses on the Guatemalan genocide—which has been labeled “acts of genocide” by the United Nations—in the context of the Guatemalan state’s weakness in mobilizing people and resources for its genocidal project. State planners were able to brutalize the indigenous population, especially during the early 1980s. But at the same time, the state showed extraordinary weakness in basic state functions such as taxing and military mobilization. The article links these failures to a more general state absence of “infrastructural capacity,” and to the strength of powerful non-state forces originating inside and outside of Guatemalan national borders. The article concludes with comparative lessons from other genocides—notably the Holocaust and Rwanda—marked by state strength in the areas of mobilizing people and resources.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.306
Teacher spread0.232 · 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