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Record W65073921

DO STANDARDIZED MANAGEMENT SYSTEMS HINDER INNOVATION PROCESSES?

2008· article· en· W65073921 on OpenAlexaff
Sandra Milena Castillo, Martí Casadesús Fa, Stanislav Karapetrović, Iñaki Heras

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Management Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWork (physics)Knowledge managementEmpirical researchOrder (exchange)Point (geometry)Process managementBusinessInnovation managementComputer scienceManagement scienceEngineering managementEngineering
DOInot available

Abstract

fetched live from OpenAlex

The aim of this research is to respond, from an empirical point of view, to the following question: "Do management systems based on standards hinder innovation processes?". In order to achieve this objective, an empirical work with the participation of 254 companies is presented here. The research was carried out in 2006 within the framework of a wider research project called "Integrated Management Systems (IMS) in Spanish Companies". Study results are presented and statistically analyzed Discussion of the research findings and future work are also provided.

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)0.023
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.099
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0020.001
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 head0.307
GPT teacher head0.505
Teacher spread0.198 · 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 designTheoretical or conceptual
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
Published2008
Admission routes1
Has abstractyes

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