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Record W7096447476

Classic Theories – Contemporary Applications: a comparative study of the implementation of innovation

2002· article· en· W7096447476 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Change and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsPopularityPublic sectorField (mathematics)ChinFocus (optics)Organizational changeField researchOrganizational culture
DOInot available

Abstract

fetched live from OpenAlex

In a classic article reviewing the field of planned change, Chin and Benne (1984) outlined three meta-approaches to the implementation of change in social and organizational contexts. These meta-theories of change – Rational-Empirical, Normative-Reeducative, and Power-Coercive – summarized the field of then-existing knowledge related to innovation at a systems level. Chin and Benne’s resulting framework summarized much of the practice in change management carried out to date and provided a framework for planning of change to be implemented over the next several decades. Research with a Public Sector focus carried out more recently (Popovich, 1998; Pozner and Rothstein, 1994) confirms that the theoretical orientations outlined in 1984 continue to be applied to the practice of innovation among modern public sector managers. This study outlines the relative popularity of each of the three meta-strategies within public sector environments within Canadian and Chinese Public Sector environments. Research interviews and literature indicate that there are significant differences, driven by culture and experience with change itself, across these two environments. Within the framework provided by Chin and Benne, current practice in a Canadian environment tends to favour a combination of Normative-

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.133
GPT teacher head0.310
Teacher spread0.177 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2002
Admission routes1
Has abstractyes

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