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Record W4308320823 · doi:10.1080/14767724.2022.2142764

How might IB classroom pedagogy ‘make a better world?’ (Toward) illuminating a promising IBDP teacher praxis

2022· article· en· W4308320823 on OpenAlexaff
John Lyons, Paul Tarc

Bibliographic record

VenueGlobalisation Societies and Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsWestern University
Fundersnot available
KeywordsPraxisPedagogySociologyMathematics educationTeacher educationPsychologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Moving beyond both a neoliberal as well as a ‘heroic’ conception of how the International Baccalaureate (IB) might ‘make a better world’, this paper focuses on the transformative potentiality of IBDP classroom pedagogy from the perspective of an experienced and critically minded educator, whose praxis has evolved across more than three decades of teaching IBDP courses in elite, well-established international schools around the world. In the IBDP teacher’s account, particular attention is placed on the relational qualities of the (ideal) classroom culture and on the tensions between learner autonomy, teacher and learner authenticity and the critical imperative to interrogate privilege. We seek to provide a generative case for researchers and educators to reflect and find greater precision on the desired ends, possibilities and limits of critical and progressive pedagogies in school classrooms under contemporary conditions constituting our ‘world in trouble’. More specifically for stakeholders of the IBDP, we offer up a promising orientation to IBDP classroom pedagogy in pursuit of the IB mission.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.024
Scholarly communication0.0120.009
Open science0.0010.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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