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Record W2547659553 · doi:10.1080/22041451.2016.1221686

A spatial grammar of organising: studying the communicative constitution of organisational spaces

2016· article· en· W2547659553 on OpenAlexafffund
Consuelo Vásquez

Bibliographic record

VenueCommunication Research and Practice · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConstitutionGrammarEmbodied cognitionSociologyPremiseSpace (punctuation)Performative utteranceSpatial organizationAction (physics)The ImaginaryCommunicative actionKnowledge managementLinguisticsComputer sciencePolitical sciencePsychologySocial scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This article contributes to the growing body of literature on organisational spaces by taking a communication-centred approach to organising that stresses a performative view of communication as constitutive of organisation. Based on this constitutive premise, I propose to study the ‘spatial grammar of organising’, which implies (a) describing the spatial imaginary of an organisation: the spatial images that are voiced and embodied, and their effects on the production of organisational spaces; and (b) attending to the processes through which these organisational spaces are performed and to their implications. Applying these analytical steps in the study of an outreach organisation’s development strategy, the article shows that the constitution of organisational spaces is a communicative process of boundary setting in which actors of various ontologies are related. Hence, the spatial imaginary of an organisation is not abstract and neutral: it has concrete organisational and political effects in defining the organisation’s space of action.

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)0.006
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.039
Scholarly communication0.0070.013
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.146
GPT teacher head0.368
Teacher spread0.221 · 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

Citations24
Published2016
Admission routes2
Has abstractyes

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