Housing Defect Assessment through Household Scale and General Contractor Level
Notice bibliographique
Résumé
Consumer dissatisfaction and damage are increasing worldwide due to the increase in defects caused by the decline in housing quality, and disputes over housing defects are expanding. The number of housing units, a representative standard related to housing quality, is used in Canada, Japan, and Korea. Generally, quality costs increase as the number of housing units increases, and each country’s laws apply stricter management standards. Therefore, the quality is expected to be better as the number of units increases. In 2020, South Korea added a new regulation requiring inspections by a quality inspection team by a public institution only when building housing complexes with more than 300 households. There is a debate about whether this direction of regulation is appropriate. This study examines whether the number of households is being used appropriately as a criterion related to housing quality. It aims to determine whether the limit of 300 households is appropriate for distinguishing housing quality. In addition, since the contractor’s role is vital in housing construction, the contractor’s capabilities and supply–demand relationship were also considered as factors affecting housing quality. The ratio of defect repair costs to construction costs was used as a quality measure for 285 housing complexes in Korea. Generally, the lower the defect repair–construction costs ratio, the better the quality. A comparative study was conducted through a variance analysis on the scale of 300 households and the status of the contractor’s capability, whether they were among the top 10 construction companies with excellent construction performance, and whether a sole contract was made. The results showed that the quality was better in the cases with 300 or more households than in the cases with fewer than 300 households. The quality was better in the cases built by higher-ranking contractors than in those built by other contractors, but there was no difference according to supply-and-demand relationships. The results of the comprehensive analysis indicated that the quality was better when higher-ranking contractors built housing complexes with 300 or more households than when lower-ranking contractors built housing complexes with fewer than 300 households. Therefore, the direction of the Korean regulation requiring quality inspections for housing complexes with more than 300 households is incorrect and should be improved to regulate housing complexes with fewer than 300 households, and of low quality. In addition, the standard of determining housing quality based solely on the number of households should be revised, and the direction should be changed to strengthen quality control and the public supervision of housing built by low-capacity contractors. If the results of this study are utilized with this view in mind, a reasonable system to protect housing consumers will be promoted.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».