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Record W7008603480

The causes of disputes that would lead to binding dispute
\nresolution methods. A perspective of the Quebec construction industry.

2020· other· en· W7008603480 on OpenAlexaboutno aff

Bibliographic record

VenueEspace École de technologie supérieure (École de technologie supérieure) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsArbitrationDispute resolutionNegotiationPerspective (graphical)Argument (complex analysis)Dispute mechanismLead (geology)Alternative dispute resolutionSustainability
DOInot available

Abstract

fetched live from OpenAlex

There are numerous causes of dispute that exist in almost every aspect of the project, and setting up a strategy to eliminate disputes from taking place in the project means literally and simply doing everything right. However, not all disputes would have the same impact on the project and the project parties, and not all dispute resolution methods (DRMs) have the same level of consequences. There is a widespread argument claim that the binding dispute resolution methods, such as arbitration, and litigation (judicial process) are the most painful dispute resolution methods in terms of the cost, time-consuming effort and the sustainability of the business relationship between the disputing parties, especially when comparing it with the softer methods such as mediation, dispute review board and negotiation (non binding DRMs). This study focuses on the causes that lead to the more hostile types of disputes among the general dispute cases, which usually produce disputes that cannot be resolved through non-binding methods and require involvement in the binding stages, such as arbitration and litigation (judicial processes), which would help the construction project parties better address such types of risks and prioritize their prevention techniques to face those threats. To meet the objectives of this study, three research questions were investigated: are disputes inevitable in construction projects?; are binding DRMs more harmful to the sustainability of business relationships and project progress than non-binding DRMs?; and what are the causes of disputes that lead to the binding DRMs stage? This study was carried out using the mixed method—exploratory sequential design, where firstly, qualitative data obtained through interviews have been collected from experts in the construction field to explore the possibility of connecting certain causes of disputes with reaching the binding stages. Then, in the second phase, quantitative data obtained through surveys have been collected in order to generalize the findings within the Quebec construction industry. The results showed that there is no statistical evidence supporting the claim that disputes are inevitable within construction projects, despite the fact that the participants in the interviews phase and the descriptive statistics of the survey results support this claim. In regard of the impact on the business relationship, the results showed that there is statistically significant evidence supporting the belief that the chances of maintaining the business relationships are high in the case of non-binding DRMs, and are low in the case of binding DRMs. With regard to the impact on the project’s work progress, the results showed that arbitration and litigation (judicial processes) are considered to be the methods with the most negative impact, while the non-binding DRMs were considered the methods with the least negative impact. With regard to the causes of dispute that are most associated with reaching binding DRMs, among 10 groups that contained 38 causes of disputes, unforeseen changes, lack of communication, ambiguities in contract documents, design errors, and delays in work progress were ones chosen as the methods connecting most with binding DRMs.

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)0.012
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.559

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0210.029
Scholarly communication0.0150.007
Open science0.0030.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.026
GPT teacher head0.316
Teacher spread0.290 · 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 designQualitative
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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