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The Use of Polyvinylchloride (PVC) Claddings and Polystyrene Wall Panels as Alternative Building Materials to Wood: A Strategy to Combat Climate Change.

2014· article· en· W1894188343 on OpenAlexvenueno aff
A.O. Ajayia, Martin Binde Gasu

Bibliographic record

VenueCanadian social science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeDeforestation (computer science)Expanded polystyreneEstateReforestationPolystyreneArchitectural engineeringEnvironmental scienceForensic engineeringBusinessMaterials scienceEngineeringComputer scienceComposite materialAgroforestryPolymer

Abstract

fetched live from OpenAlex

Unprecedented variations in climate are currently being experienced all over the world and Nigeria is not an exemption from this global trend.  Generally, researchers have pointed to human activities as the major contributor. The paper evaluates occupants’ perception and acceptability of Polyvinylchloride (PVC) claddings and Polystyrene wall units as substitutes for wood based products at Royal Estate in Lagos.This paper also examines alternative building materials as a remedy to deforestation in building construction activities in Nigeria with a view to highlighting their mutilating effect on climate change. A total of 20 dwelling units were studied; using Post Occupancy Evaluation (POE) research method. Results show that 90% of respondents rated as ‘good’ their level of acceptability and awareness of these materials while quality and durability were rated equally as ‘good’ by 75% of total respondents.From the general high level of acceptability of Polyvinylchloride (PVC) claddings and Polystyrene wall units, if popularized could serve as alternative building materials. This may reduce the dependence on wood which could therefore, mitigate against the negative impact of climate change.Government has been advised to make and implement reforestation policies so that trees could serve as carbon sink.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
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 head0.082
GPT teacher head0.312
Teacher spread0.230 · 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.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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