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Record W1939526602 · doi:10.1111/1468-5973.12030

Interorganizational Dynamics and Characteristics of Critical Infrastructure Networks: The Study of Three Critical Infrastructures in the <scp>G</scp>reater <scp>M</scp>ontreal Area

2013· article· en· W1939526602 on OpenAlex
Anaïs Valiquette L’Heureux, Marie‐Christine Therrien

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Contingencies and Crisis Management · 2013
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Resilience and Vulnerability Analysis
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsInterdependenceCritical infrastructureResilience (materials science)Contingency theoryNormativeContingencyBusinessOrganizational structureKnowledge managementComputer scienceComputer securitySociologyEconomicsManagementPolitical science

Abstract

fetched live from OpenAlex

This study applies a strategic framework for assessing organizational and network resilience of 75 critical infrastructure ( CI ) players in the G reater M ontreal area. It identifies the challenges to these CI s' resilience. Contingency analysis is used to describe the main tendencies regarding values, practices, rules and norms, communicational and decisional structures as well as the interdependencies and their institutional, normative and economic contexts. This article examines three well‐known CI networks: transportation, energy and telecommunication, comprising governmental, community and private‐sector organizations. To do so, we developed a survey instrument to collect data from hundreds of critical infrastructure managers. Our findings indicate discrepancies in internal and external resilience factors across organizational type, size and CI .

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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