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Record W4380481499 · doi:10.14324/ijdegl.15.1.04

Situating Daisaku Ikeda’s essential elements of global citizenship within contemporary scholarship: a qualitative meta-synthesis

2023· article· en· W4380481499 on OpenAlexaff
Paul D. Sherman, Olivia Boukydis

Bibliographic record

VenueInternational Journal of Development Education and Global Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsScholarshipCitizenshipGlobal citizenshipSubject (documents)SociologyQualitative researchEpistemologyEnvironmental ethicsSocial sciencePolitical scienceLawPhilosophyPoliticsLibrary scienceComputer science

Abstract

fetched live from OpenAlex

This article reports on meta-synthesis research that examined contemporary scholarship on global citizenship for the purpose of identifying a possible alignment with Daisaku Ikeda’s views on global citizenship. Thirty relatively contemporary scholarly articles on the subject matter were examined using a qualitative meta-synthesis methodology. Ikeda’s speech entitled ‘Thoughts on education for global citizenship’, delivered over 25 years ago at Columbia University’s Teachers College, USA, contains his most frequently cited ideas on the salient conditions required for global citizenship. As Ikeda is a thoughtful and prolific author on the subject of global citizenship, there is merit in exploring the alignment of his ideas about this concept with those articulated in contemporary scholarship. Conducting a meta-synthesis through the lens of Ikeda’s essential elements of global citizenship has helped to identify potentially useful contributions to the global citizenship discourse. This article highlights salient common themes of global citizenship uncovered through the meta-synthesis research, as well as providing an alternative definition of global citizenship gleaned from the findings.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.112
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.441
Teacher spread0.342 · 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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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