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Record W1507907600 · doi:10.1287/orsc.1120.0792

Temporal Work in Strategy Making

2012· article· en· W1507907600 on OpenAlexaff
Sarah Kaplan, Wanda J. Orlikowski

Bibliographic record

VenueOrganization Science · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsConstruct (python library)Action (physics)Work (physics)Status quoField (mathematics)Management sciencePolitical scienceComputer scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

This paper reports on a field study of strategy making in one organization facing an industry crisis. In a comparison of five strategy projects, we observed that organizational participants struggled with competing interpretations of what might emerge in the future, what was currently at stake, and even what had happened in the past. We develop a model of temporal work in strategy making that articulates how actors resolved differences and linked their interpretations of the past, present, and future so as to construct a strategic account that enabled concrete strategic choice and action. We found that settling on a particular account required it to be coherent, plausible, and acceptable; otherwise, breakdowns resulted. Such breakdowns could impede progress, but they could also be generative in provoking a search for new interpretations and possibilities for action. The more intensely actors engaged in temporal work, the more likely the strategies departed from the status quo. Our model suggests that strategy cannot be understood as the product of more or less accurate forecasting without considering the multiple interpretations of present concerns and historical trajectories that help to constitute those forecasts. Projections of the future are always entangled with views of the past and present, and temporal work is the means by which actors construct and reconstruct the connections among them. These insights into the mechanisms of strategy making help explain the practices and conditions that produce organizational inertia and 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 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)0.007
metaresearch head score (Gemma)0.006
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 score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.016
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.196
GPT teacher head0.428
Teacher spread0.232 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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