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Record W4283267575 · doi:10.18357/bigr32202220358

The Border-Development-Climate Change Nexus: Precarious Campesinos at the Selva Maya Mexico–Guatemala Border

2022· article· en· W4283267575 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueBorders in Globalization Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversité de Sherbrooke
FundersGlobal Challenges Research FundConsejo Nacional de Ciencia y Tecnología
KeywordsNexus (standard)Climate changeGeographyMayaPsychological interventionPolitical scienceScope (computer science)Development economicsEconomic growthEnvironmental resource managementEcologyEconomicsArchaeology

Abstract

fetched live from OpenAlex

Borderlands can be places of socio-economic tensions, development challenges, and ecological risks, now exacerbated by climate change. We investigate the border-development-climate change nexus using research from Calakmul, Mexico and Petén, Guatemala, to detail the lived experiences and vulnerabilities of campesinos in the Selva Maya cross-border region. Our mixed methods approach combines historical analysis and ethnographic interviews with 70 campesinos. We demonstrate how large scale development approaches result in local and specific policy interventions, but produce mixed outcomes for campesinos, neglecting the most marginalized. Despite the absence of any major border crossings, a porous border in this area allows flows of people, goods, and services to connect the region, but there are differential national outcomes. In Petén, many campesinos suffer from ‘irregularity’ (lacking rights to the lands where they live and cultivate), preventing access to state development benefits. In Calakmul greater climate change demands adaptations beyond the scope of recent policy interventions. We consider how the border region includes biophysical processes as well as socio-political and cultural ones, and we argue that policy interventions are required at global, national, and local scales to address structural inequalities and co-create local solutions to development, migration, and climate change challenges.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.791
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.353
Teacher spread0.331 · 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