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Record W3118838891 · doi:10.1109/emr.2021.3049158

A Rising Tide Lifts All Boats, Ignoring Risks Can Sink Them: The Peril of Rework in Large-Scale Transport Projects

2021· article· en· W3118838891 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Engineering Management Review · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Ottawa
FundersAustralian Research Council
KeywordsReworkScale (ratio)BusinessPublic sectorRisk analysis (engineering)Work (physics)Private sectorOperations managementIndustrial organizationEngineeringEconomicsEconomyEconomic growth

Abstract

fetched live from OpenAlex

Rework can be a significant and costly problem during the construction of large-scale transport (>$500 million) projects. There is, however, limited understanding and knowledge about the underlying dynamics and causal mechanisms of rework. Both the public and private sector organisations tend to ignore the costs of rework and thus have been unable to contain and manage its risks. This article takes a look at the wicked and inter-organizational problem of rework and invites the public and private sectors to work in unison to thwart this risk. The paper makes a twofold contribution: (1) it calls on the public and private sectors to consider the likelihood of rework as a part of their risk management strategy; and (2) suggests that there is need use a smart data approach to ‘anticipate what might go’ wrong in terms of rework so as to deliver large-scale transport projects successfully.

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.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.110
GPT teacher head0.343
Teacher spread0.234 · 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