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Record W1485377278 · doi:10.1108/joepp-09-2014-0060

Complexity and ethical crisis management

2014· article· en· W1485377278 on OpenAlexaff
Yoann Guntzburger, Thierry C. Pauchant

Bibliographic record

VenueJournal of Organizational Effectiveness People and Performance · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMindsetCrisis managementValue (mathematics)Context (archaeology)Knowledge managementBusinessPolitical sciencePublic relationsComputer scienceEconomicsManagement

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to analyse the Fukushima nuclear disaster (FND) that occurred 11 March 2011 through the lens of the systemic and complexity theory. This analysis allows the proposition of some guidelines for the development of a more preventive and ethical approach in crisis management, including changes in human resource management and training. Design/methodology/approach – Thanks to a layered analysis of the complex system that represents the FND and an actor/stake approach, this paper sheds light on the many failures that occurred on the personal, organizational, institutional, political and cultural level. Findings – This analysis highlights that, beyond the apparent simplicity of the natural trigger events, a complex network of legal, cultural and technological paradigms, as well as the defense mechanisms of personal and organizational moral disengagement, have structured the context of this crisis, allowing for an event to turn into this disaster. Practical implications – This study shows the limit of classical approach towards crisis management such as probabilistic risk assessment in terms of systemic and complexity: the assessment could be easily overcome if the mindset of the organization leaders is not already oriented towards preventive management. Originality/value – The value of this study is participating to the effort of showing the need to develop more preventive mindsets and behaviours in the global economy, dealing with worldwide and complex issues.

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)0.010
metaresearch head score (Gemma)0.018
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.034
Scholarly communication0.0090.006
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.292
Teacher spread0.277 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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