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Record W3045968789 · doi:10.12821/ijispm020402

Governance challenges in temporary organizations: a case of evolution and representations

2022· article· en· W3045968789 on OpenAlexaff
Magali Simard, Danielle Laberge

Bibliographic record

VenueInternational journal of information systems and project management · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsOperationalizationCorporate governanceProject governanceBusinessDiversity (politics)Public relationsMulti-level governanceProcess managementPolitical sciencePublic administrationLawFinance

Abstract

fetched live from OpenAlex

According to the literature, formal project governance often stops at the steering committee, which is also identified as the main link between the permanent and temporary organizations. Generally, top managers play an active role as sponsors in this committee until the project is approved and launched. Afterwards, the project execution is usually delegated, enabling middle managers to participate in strategy operationalization. As such, they are likely to take part in the project governance and its operationalization. In this study, we are especially interested in the governance zone reporting to the steering committee. Within this zone, formal and informal governance is intertwined, and there is likely to be considerable overlap with the permanent organization. Our study focuses on a specific liaison device within this zone: the Project Coordination Committee, which has rarely been studied. We explore how project governance evolves and is represented by project participants. Our results show a surprising diversity in participants’ representations. This allows us to identify a number of conclusions that go beyond the governance form issues and relate to the complexity of this governance zone and its influence on the disruptions between permanent and temporary governance structures within a large organization.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.344
Teacher spread0.288 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations4
Published2022
Admission routes1
Has abstractyes

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