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Record W2485250302 · doi:10.5539/jpl.v9n6p112

City and Urban Social Justice, Analyzing and Evaluating Regional Inequalities (Case Study: Eight Urban Deteriorated Districts of Zahedan City)

2016· article· en· W2485250302 on OpenAlexvenueno aff
Fereshte Sheybani Moghadam, Behrouz Darvish, Tayebeh Sargolzaee Javan

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyUrbanizationPer capitaPopulationSample (material)Distribution (mathematics)SocioeconomicsInequalityUrban planningEconomic growthSociologyDemographyEconomicsMathematics

Abstract

fetched live from OpenAlex

Dissolution of distribution system of urban services centers has been one of the most important consequences of the rapid growth of urbanization and physical development of Iranian cities within recent decades. It has brought about social inequalities for citizens in terms of taking advantage of such services. The public urban services forms the physical, social and spatial nature of a city; hence, unfair distribution of such services will impose an irrecoverable influence on both the structure and nature of the city and class-based segregation of districts of the city on the one hand and has brought about serious challenges for the urban management. This study tries to explain life quality levels in the urban deteriorated fabric of Zahedan City based on 38 life quality indexes and their relationship with the urban land uses per capita across different districts; 10-use per capita has been used. Over-18-year-old citizens living in deteriorated districts of Zahedan City constitutes population of this study. Totally 258789 people live in such districts. A total of 384 people were selected as the sample of the study using random sampling and Cochran’s formula. A descriptive-analytical method was followed to conduct the study. Initially, exploratory studies and preliminary visits were arranged and then it was followed by the field study, using survey method. Entropy and COPRAS methods were used to determine the sample size of the questionnaires given population of each district and finally to analyze and rank districts. The results showed that per capita distribution of urban services across the districts 4, 3 and 5 was better than the standard per capita issued by the Ministry of Housing and Urban Development and they were closer to the ideal condition. However, there was a large gap between distribution per capita in districts 2, 1, 7 and 8 and the standard per capita and the positive ideal and they have not ideal condition. According to the life quality indexes, accessing to primary schools is the most important item for the citizens and this item is not ideal in these districts and is the first item in the urban services accessibility indexes. Finally, the results of rating districts based on urban per capita and life quality indexes indicate that there is a weak relationship between urban per capita and life quality indexes; as only a district out of eight ones showed an equal rate.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.104
GPT teacher head0.387
Teacher spread0.283 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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