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Assessing and Managing the Potential Environmental Risks of Construction Projects

2005· article· en· W2108102148 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePractice Periodical on Structural Design and Construction · 2005
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIndemnityRisk analysis (engineering)LiabilityPlan (archaeology)BusinessRisk managementIdentification (biology)Environmental planningConstruction managementAction planEnvironmental impact assessmentEnvironmental resource managementEngineeringCivil engineeringFinanceActuarial science

Abstract

fetched live from OpenAlex

Policy makers make key decisions regarding economic development, but engineers are central to the implementation of these policies. With the realization that economic development and environment are interlinked, engineers are well advised to ensure avoidance of adverse impacts on society and environment by adopting better practices during the design and implementation of construction projects. The objective of this paper is to present a project’s proponents and construction contractors with a framework to identify the environmental risks early in a project’s life so that a proper plan could be developed to mitigate the impact of them. The paper also discusses options currently available in Canada for environmental-type insurance and contractual liability indemnity clauses. A survey conducted among construction companies to assess current risk-management practices in the construction industry show that although many companies are concerned about the possible implications of environmental risks to their project, there still needs to be more emphasis on identification and mitigation of these risks and the need to have a comprehensive framework to properly identify and develop an action plan for environmental related risk issues. The current research trends to achieve these objectives are also outlined in the paper.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
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 head0.120
GPT teacher head0.391
Teacher spread0.271 · 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