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Record W3025982040 · doi:10.1080/19186444.2020.1764326

He who defends everything, defends nothing: proactivity in organizational resilience

2020· article· en· W3025982040 on OpenAlexaffvenue
Neil Cruickshank

Bibliographic record

VenueTransnational Corporation Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsCarleton University
Fundersnot available
KeywordsProactivityResilience (materials science)Perspective (graphical)NothingFunction (biology)Shock (circulatory)Variety (cybernetics)BusinessPsychological resiliencePublic relationsPsychologyPolitical scienceSocial psychologyComputer scienceEpistemologyMedicinePhilosophyPhysics

Abstract

fetched live from OpenAlex

Organisational resilience is most often defined as the ability to function during a shock and then return to normal function; consequently, it has been studied from the perspective of organisational disciplines closely related to crisis and crisis-recovery, such as supply-chain management and risk management. However, increasing complexity and the volume, variety and velocity of shocks has created an environment where the organisation must proactively and continuously demonstrate resilience, through the cultivation of anticipatory innovation.

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)0.013
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0010.005
Scholarly communication0.0040.007
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.244
Teacher spread0.212 · 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

Citations17
Published2020
Admission routes2
Has abstractno

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