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Record W3209236142

Exploring the Relationship Between the Framing of Cultural Diversity and the Strategies Used in its Management Among Educational Leaders

2020· article· en· W3209236142 on OpenAlexaff
Derek Martin

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsNipissing University
Fundersnot available
KeywordsFraming (construction)Cultural diversityDiversity (politics)SociologyDiversity managementPublic relationsSocial psychologyPsychologyPolitical scienceGeographyAnthropology
DOInot available

Abstract

fetched live from OpenAlex

Educational leaders have influential roles in their institutions, including how cultural diversity is managed. Some scholars have examined the relationship between how educational leaders frame cultural diversity and patterns in their leadership behaviour. One way that this is done is by applying the concepts of multiculturalism types and leadership styles. Some studies have suggested that certain multiculturalism types, or approaches to cultural diversity, are associated with certain leadership styles. For example, conservative multiculturalism, or a cultural-deficit approach, is associated with a transactional leadership style. Liberal multiculturalism, or a culture celebration approach to diversity, is associated with a social justice or critical leadership style that seeks to understand and address inequalities and injustices. This research approach is instructive, but it may benefit from an expanded view of the factors that affect the actions of educational leaders, for example the norms and values of an organization, community, or sector.

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)0.011
metaresearch head score (Gemma)0.027
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: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.822
GPT teacher head0.597
Teacher spread0.225 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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