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Record W4328098755 · doi:10.1177/01708406231166807

When Time Falls Apart: Re-centring human time in organisations through the lived experience of waiting

2023· article· en· W4328098755 on OpenAlexaff
Catherine Bailey, Roy Suddaby

Bibliographic record

VenueOrganization Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Victoria
FundersBritish Academy
KeywordsTemporalitiesTemporalityCentringPerspective (graphical)SociologyAestheticsEpistemologyPsychologyComputer sciencePolitical scienceVisual artsArtArtificial intelligenceLaw

Abstract

fetched live from OpenAlex

Research on the lived experience of organisational temporalities has thus far overlooked the potential significance of what happens in the interstices that arise between temporal structures. To address this gap, we examined how individuals in three occupations experienced one such interstitial temporal form: waiting. Our analysis of waiting time uncovers two distinct and overarching temporal macro-structures that govern how workers use and experience time in organisations: intensified-organisational – the speeded-up, intensified temporality of modern forms of work organisation – and adaptive-organic , that represents natural and human temporalities. Waiting emerges as a paradoxical temporal experience which individuals simultaneously welcome yet seek to eliminate; one that stands outside temporal structures yet serves to reinforce them. From a human perspective, waiting furnishes moments during which time can be ‘undone’, affording us micro-moments to reclaim and re-centre time in organisations as human time.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.056
GPT teacher head0.279
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations23
Published2023
Admission routes1
Has abstractyes

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