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Record W3035829093 · doi:10.1177/0021886320933736

The Power of the Platform: Place and Employee Responses to Organizational Change

2020· article· en· W3035829093 on OpenAlexaff
Inger G. Stensaker, Julia Balogun, Ann Langley

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsSensemakingConstruct (python library)NarrativeMerge (version control)Organizational changeBusinessOrganizational identityChange management (ITSM)Public relationsKnowledge managementOrganizational commitmentMarketingPolitical scienceComputer scienceLean manufacturing

Abstract

fetched live from OpenAlex

This inductive study explores how place influences collective sensemaking and employee responses during organizational change. The empirical setting of our study is an offshore oil platform undergoing changes that involve standardizing operational practices and relocating personnel as two organizations merge. We analyze the narratives of two employee groups and show how employees located onshore construct progressive change narratives, enabling them to adapt to change, while employees located on the offshore oil platform construct regressive narratives leaving them romanticizing the past and struggling to accept change. Our findings illustrate how the manipulation, reconfiguration, and exploitation of place has implications for employees’ capacities to accept and adapt to change.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.005
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.260
Teacher spread0.213 · 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 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

Citations11
Published2020
Admission routes1
Has abstractyes

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