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Record W2974302450

Exploring Teachers’ Notions of Global Citizenship Education in the US-Mexico Border

2019· article· en· W2974302450 on OpenAlexaff
Marco Aurelio Navarro-Leal, Lidia Celia Colmenares-González

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsCitizenshipGlobal citizenship educationPolitical scienceGlobal citizenshipSociologyCitizenship educationPedagogyMathematics educationPsychologyLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the notions that teachers in the US-Mexican border have about global citizenship education; the specific research questions were: do these notions refer to an education that leads to action? Or to an active sense of citizenship? Do these notions contain a global scope? It was expected that living in the border, their daily exposition to an international experience would lead notions to a global perspective. Five teachers of normal schools were interviewed, and their notions were grouped into three main ideas: with the highest consensus there were values; second, normative life; and third, some aspects related to community life. Although some of the findings express notions of an active citizenship, there was nothing related to a global scope of citizenship. The explanation could be that their notions of citizenship are highly influenced by local concerns about insecurity, leaving aside a global perspective.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.014
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.011
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0010.003
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 head0.383
GPT teacher head0.597
Teacher spread0.214 · 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
Published2019
Admission routes1
Has abstractyes

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