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Record W4394814371 · doi:10.5772/intechopen.1005130

Hearts of Courage, Faces of Peace: Rebuilding and Resistance in Post-Dictatorship Honduras

2024· book-chapter· en· W4394814371 on OpenAlexaboutno aff
Matt Bereza

Bibliographic record

VenueIntechOpen eBooks · 2024
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersWorld Health Organization
KeywordsDictatorshipPresidencyPolitical scienceDemocracyCapital (architecture)SovereigntyEconomic JusticePoliticsAusterityResistance (ecology)Political economyLawSociologyGeography

Abstract

fetched live from OpenAlex

This chapter explores and describes the complex tapestry of peace and the challenges that have emerged in Honduras following the era of dictatorship. It aims to shed light on the nation’s path towards the establishment of democratic institutions amid a backdrop of political and economic turmoil. The research is based on an investigative journey through Honduras, exploring four distinct regions, each with its unique story and struggle. In the Aguán Valley, the focus is on the community’s fight against extractive corporations, highlighting the campesinos’ defense of their land from the encroachment of palm oil magnates. The Island of Roatán offers insights into the Garifuna’s efforts to safeguard their territories from the ambitions of developers. Meanwhile, Choloma serves as a view into the textile workers’ challenges, encompassing their labor difficulties. Lastly, the capital city, Tegucigalpa, provides a stage for engaging with a beverage union, and discussions with the US and Canadian embassies and governmental representatives surrounding the Castro presidency and progress. Through this comprehensive examination, the chapter endeavors to present an overarching view of Honduras’ continued struggle for peace, sovereignty, and justice in the aftermath of dictatorial governance.

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 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: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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