MétaCan
Menu
Back to cohort

Organization Theories in the Making

2022· book· en· W4306863326 on OpenAlexaff
Linda Rouleau

Bibliographic record

Venuenot available
Typebook
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsPerspective (graphical)Field (mathematics)Table of contentsConventionSociologyEngineering ethicsEpistemologyComputer scienceSocial scienceEngineeringWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract This book aims to demonstrate how, over the past 25 years, the field of organization theories (OTs) has been providing stimulating, thoughtful, and innovative perspectives. Junior researchers and PhD students will find everything they need to know about key academic conversations central to the field today. The book offers a selective immersion in organizational institutionalism, convention analysis, network analysis, knowledge studies, discourse studies, and practice studies. For each of these perspectives, the book explores its different research streams and zooms in on the research communities that give rise to them. In addition, it highlights how these perspectives all intersect with each other to form a mosaic of ideas that define today’s organizations. This book also invites early career researchers and graduate students to learn how recent theories view and portray the organization and, more specifically, to understand current research questions, conceptual resources, and methods. A deep knowledge of recent OTs is key when building a compelling literature review and making meaningful theoretical contributions. This book offers readers the opportunity to develop their theory-building skills and more by taking a deep dive into the complexities and controversies of OTs. The main arguments of each perspective are illustrated by specific exemplars from academic journals. Each chapter contains a synoptic table summarizing the main scholarly components within each perspective and its research substreams.

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)0.006
metaresearch head score (Gemma)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.162
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0400.001

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 head0.133
GPT teacher head0.392
Teacher spread0.260 · 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 designTheoretical or conceptual
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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicComplex Systems and Decision MakingFrench-language works237,207