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Record W4391030618 · doi:10.1080/09692290.2023.2285871

Globalize IPE, not just the syllabi! Virtual classrooms interactions and the making of the Atlantic Diagonals glossary

2024· article· en· W4391030618 on OpenAlexfundno aff
Jean‐Christophe Graz, Jean-Marie Chenou, Carolina Urrego-Sandoval, Sylvain Maechler

Bibliographic record

VenueReview of International Political Economy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
FundersUniversité de LausanneUniversity of WarwickUniversidad de los AndesUniversité du Québec à Montréal
KeywordsSyllabusSociologyCompetence (human resources)PoliticsGlossaryPedagogyPolitical scienceLinguisticsLawManagementEconomics

Abstract

fetched live from OpenAlex

How do we as scholars and instructors globalize International Political Economy (IPE) teaching beyond the syllabi? This pedagogical intervention proposes a concrete way to globalize IPE teaching in the classroom and through student-led activities based on courses taught during two semesters at the Universities of Lausanne (Switzerland) and Los Andes (Bogota, Colombia). We present the making of a multilingual glossary of IPE drafted by groups of students based in different universities in very different geographical, political, economic and cultural contexts. We argue that such a pedagogical intervention is not only about globalizing and decolonizing the teaching of IPE; it also helps develop important competences by students, especially their engagement and criticality. We review the literature on globalizing and decolonizing IPE before providing background on the idea of ‘global competence’ as part of the objectives of higher education and its relevance for recent calls to globalize IPE. We then present a toolbox for the pedagogical intervention that we used in such a way to be reused by anyone wanting to build upon it. Lastly, we further reflect on the contribution and challenges of such interventions regarding current attempts to globalize and decolonize IPE.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.035
GPT teacher head0.391
Teacher spread0.356 · 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 designNot applicable
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

Citations2
Published2024
Admission routes1
Has abstractyes

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