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Record W2031551247 · doi:10.5539/ass.v11n10p202

Associations between Dwelling Type, Environmental Aspects of Housing Welfare, and Residents’ Sense of Insecurity in Bandar-Abbas, Iran

2015· article· en· W2031551247 on OpenAlexvenueno aff
Behrang Moradi, Farimah Dokoushkani, Asbah Razali, Seyed Mehdi Motevaliyan, Bahare Fallahi

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPlace Attachment and Urban Studies
Canadian institutionsnot available
Fundersnot available
KeywordsApartmentWelfareFeelingRecreationSocioeconomicsPsychologyBusinessDemographic economicsSocial psychologySociologyPolitical scienceEconomicsEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Recently, feeling of safety in the residential area as a component of a proper housing has attracted a lot of attention from psycho-sociologist. Hence, this survey aims at determining the relationship between dwelling type, environmental aspects of housing welfare, and residents’ sense of insecurity in Bandar-Abbas, Iran using a self-administered structured questionnaire distributed among 384 residents (62 from single-unit houses + 322 from apartment complexes) randomly selected. The findings show that dwelling type is significantly related to sense of insecurity among the residents. Further, the relationship between the components of housing welfare in residential building and residents’ sense of insecurity is negatively significant. Additionally, regarding the effect of housing welfare components in residential neighborhood, only the access to recreational services has a significant negative but small effect on the sense of insecurity. Therefore, the factors which contribute to improved residents’ feeling of safety may absorb more attention by both designers and policy makers in the housing development in order to increase the welfare of housing.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.320
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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