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Change Order Clauses in Standard Contract Documents

2016· article· en· W2230896697 on OpenAlexaboutno aff
Matt Syal, Mrs. Shraddha Bora

Bibliographic record

VenuePractice Periodical on Structural Design and Construction · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)Change orderConfusionConstruction contractProfit (economics)Contract managementBusinessOverhead (engineering)Process (computing)Joint (building)Actuarial scienceComputer scienceOperations managementOperations researchEconomicsFinanceManagementEngineeringProject managementMarketingCivil engineeringMicroeconomics

Abstract

fetched live from OpenAlex

This paper provides details and a comparative review of change-order-related clauses in major standard contract agreements. The information from the review is used to highlight the impact of the contractual agreements and their general conditions on change order procedures and pricing. The main categories of analysis include the change order process, direct and overhead cost items, and overhead and profit practices and percentages. Four sets of standard contract documents are reviewed: American Institute of Architects (AIA) A201-2007 and A401-2007, ConsensusDocs 200 and 750, Engineers Joint Contract Document Committee (EJCDC) C-700 and C-523, and Canadian Construction Documents Committee (CCDC) 2-2008/Canadian Construction Association (CCA) 1-2008. The comparative review points to the prevailing confusion and conflicts related to change order procedures and pricing among owners, designers, general contractors, construction managers, and subcontractors.

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)0.058
metaresearch head score (Gemma)0.176
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.058
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.176
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0190.033
Science and technology studies0.0020.005
Scholarly communication0.0080.007
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.099
GPT teacher head0.388
Teacher spread0.289 · 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 designNot applicable
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

Citations18
Published2016
Admission routes1
Has abstractyes

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