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Record W7060029181

9781000479515.pdf

2021· other· en· W7060029181 on OpenAlexfundno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2021
Typeother
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNational Science Foundation
KeywordsCorporate governanceReading (process)Compliance (psychology)Reflection (computer programming)Business ethicsEthical codeGood governance
DOInot available

Abstract

fetched live from OpenAlex

This book fills an important gap in the sport governance literature by engaging in critical reflection on the concept of ‘good governance’. It examines the theoretical perspectives that lead to different conceptualisations of governance and, therefore, to different standards for institutional quality. It explores the different practical strategies that have been employed to achieve the implementation of good governance principles. The first part of the book aims to shed light on the complexity and nuances of good governance by examining theoretical perspectives including leadership, value, feminism, culture and systems. The second part of the book has a practical focus, concentrating on reform strategies, from compliance policies and codes of ethics to external reporting and integrity systems. Together, these studies shed important new light on how we define and understand governance, and on the limits and capabilities of different methods for inducing good governance. With higher ethical standards demanded in sport business and management than ever before, this book is important reading for all advanced students and researchers with an interest in sport governance and sport policy, and for all sport industry professionals looking to improve their professional practice.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.961
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9610.737

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 head0.008
GPT teacher head0.220
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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
Published2021
Admission routes1
Has abstractyes

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