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Organisational socialisation in a crisis context

2009· article· en· W1966219702 on OpenAlexafffundabout
Carole Lalonde

Bibliographic record

VenueDisasters · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversité LavalSNC-Lavalin (Canada)
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsContext (archaeology)Crisis managementExploratory researchPublic relationsSocializationSociologyField (mathematics)Political sciencePsychologySocial scienceLawGeography

Abstract

fetched live from OpenAlex

The objective of this paper is to highlight the dimensions characterising the socialisation process in a crisis context. Based on the definition of organisational socialisation advanced by Van Maanen and Schein (1979) and employed later by Jones (1986), a crisis is presented as a passage from a 'normal' situation to an 'exceptional' situation. A crisis represents a socialisation context in the sense that it is a novel state in which actors must develop a different way of mobilising their knowledge, utilising their skills, and practicing their trade or profession. The paper discusses certain findings that have emerged from the literature on organisational socialisation, as well as from the testimony of actors who participated in efforts to manage the Quebec ice-storm crisis of early 1998. It is hoped that this exploratory study's data will give rise to fruitful interaction between the field of organisational socialisation and that of crisis management.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.030
Scholarly communication0.0080.006
Open science0.0010.012
Research integrity0.0010.002
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 head0.019
GPT teacher head0.304
Teacher spread0.285 · 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 designQualitative
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

Citations14
Published2009
Admission routes3
Has abstractyes

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