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Record W4238332427 · doi:10.5206/cie-eci.v45i1.9285

Mathematics as a Cultural Role Player in School Development: Perspectives from the East and West

2016· article· en· W4238332427 on OpenAlexafffundvenueabout
Anthony N. Ezeife

Bibliographic record

VenueComparative and International Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Windsor
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Windsor
KeywordsSustenanceRealmHarmony (color)CurriculumSociologyPedagogySociocultural evolutionMathematics educationPsychologyPolitical science

Abstract

fetched live from OpenAlex

In all societies and civilizations, schools are set up primarily to offer and promote socially valued knowledge, experiences, skills, and attitudes geared toward the sustenance and further enrichment of societal norms and goals. Since schools are charged with this weighty responsibility, harnessed and purposeful school development is essential for the achievement of cherished societal goals. Several intertwining factors such as culture, equity, diversity and multiculturalism, etc., contribute to meaningful school development in every society. In the order of hierarchical importance amongst these factors, culture ranks topmost in the list because it (culture) plays a deep and pervasive role in school learning, and by extension, in societal development and harmony. But what is culture? Hollins (1996, p. 18) succinctly defines culture as “the body of learned beliefs, traditions, and guides for behaviour that are shared among members of any human society”. In the realm of mathematics education, the learner’s culture has been identified as one of the factors that strongly influence and shape learning and performance. In pursuit of one of the set goals (cultural perspectives) of the Mathematics Research Team of the Canada-China Reciprocal Learning Project, this paper delves into the interactions of culture, the environment, and development/implementation of the mathematics curriculum in the East-West learning environments.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.269
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.087
GPT teacher head0.401
Teacher spread0.314 · 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
Published2016
Admission routes4
Has abstractyes

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