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Record W4398294874 · doi:10.7910/dvn/n2fdd2

Aproximación Social del Contrabando en la Zona del Campo de Gibraltar

2022· dataset· en· W4398294874 on OpenAlexaff
L. Lozano, José Javier García Cardenas

Bibliographic record

VenueHarvard Dataverse · 2022
Typedataset
Languageen
FieldSocial Sciences
TopicLabor Law and Work Dynamics
Canadian institutionsAUG Signals (Canada)
Fundersnot available
KeywordsHumanitiesGeographyCartographyArt

Abstract

fetched live from OpenAlex

I am about to pose a series of questions to a number of controversial notions. Campo de Gibraltar, is it the gateway to Europe for smuggling, smugglers, has it become a role model for the new generations in the area? Is Spain the country with the most drug seizures in the world? The Port of Algeciras is the fourth largest in Europe, during the years 2017 to 2020 a transit of 107.3 million tonnes of goods per year was recorded. Fourteen kilometres separate the African continent from Spain, making it the most important route for migration and drug trafficking from Morocco. The Campo de Gibraltar is a geo-strategic and socio-economically disadvantaged area, its two very different borders, with very different societies, offer smugglers tangible support. keywords: smuggling, drug trafficking, mythologising, Strait of Gibraltar, geostrategic.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.012

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 head0.010
GPT teacher head0.270
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreDataset

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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