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List of Contributors

2012· other· en· W4242580962 on OpenAlexaff

Bibliographic record

VenueAdvances in educational administration · 2012
Typeother
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPublishingCitationValue (mathematics)Transformational leadershipNarrativeLibrary scienceSociologyPedagogyComputer sciencePolitical sciencePublic relationsArt

Abstract

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Citation (2012), "List of Contributors", Miller, F.S. (Ed.) Transforming Learning Environments: Strategies to Shape the Next Generation (Advances in Educational Administration, Vol. 16), Emerald Group Publishing Limited, Leeds, pp. vii-viii. https://doi.org/10.1108/S1479-3660(2012)0000016002 Publisher: Emerald Group Publishing Limited Copyright © 2012, Emerald Group Publishing Limited Book Chapters Transforming Learning Environments: Strategies to Shape the Next Generation Advances in Educational Administration Advances in Educational Administration Copyright Page List of Contributors Acknowledgment Introduction Developing Teacher Leaders to transform Classrooms, Schools, and Communities Leading for Change: Designing a Model of Transformational Leadership Through the Carnegie Project on the Education Doctorate Teaching about Religious and Spiritual Difference in a Global Society Incorporating Concepts of Global Citizenry into Student-Centered Academic Advising Collaborative Partnerships for Capacity Building through Professional Development Learning Starts with Design: Using Universal Design for Learning (UDL) in Higher Education Course Redesign The Value of Value-Added Methods Responsive Technologies for Young Adolescents “This I Believe”: Addressing Cultural Competency with the Digital Narratives of Middle Grades English Language Learners From Pong to PS3: How Video Games Enhance Our Capacity to Learn and Build Community Game Changers for Transforming 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.754
Threshold uncertainty score0.986

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)0.0150.000

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 head0.026
GPT teacher head0.400
Teacher spread0.374 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes1
Has abstractyes

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