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Record W1985643230 · doi:10.2495/sdp-v4-n2-112-122

Community development in the east prefecture of Attica, Greece, following the 2004 Summer Olympic Games of Athens

2009· article· en· W1985643230 on OpenAlexvenueno aff
Helen Theodoropoulou, Malvina Vamvakari, Roιdo Mitoula

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyTourismReal estateInvestment (military)Rural areaPopulationSocioeconomicsSample (material)Economic growthRegional scienceBusinessPolitical scienceDemographyEconomicsFinance

Abstract

fetched live from OpenAlex

The present study examined how community development has been affected by social and economic changes in four specifi c semi rural areas which are located in the east prefecture of Attica in Greece.These semi rural areas are affected signifi cantly by social and economic changes, because of substantial new infrastructure development that took place in relation to the 2004 Summer Olympic Games of Athens.The aim of this study was to examine local entrepreneurship as well as local social and economic development in the study areas.Sample data were collected on the characteristics of residents and local enterprises and land use changes in these four areas of Attica.On the basis of these data a profi le of the residents and the characteristics of land use and local enterprises were constructed.The results of the study showed that there has been a substantial population increase and real estate construction.Also, residential land has increased at the expense of farmland.Furthermore, new enterprises are founded through private investments, which increase local entrepreneurship.Using cross-tabulation statistical methods it was found that the educational level of the responders is positively related with the occupation satisfaction (P = 0.0345).Also, the more an area was developed the more pharmacies existed in the specifi c area (P = 0.0437) and the closest an area was from the sea the more tourist character it had (P = 0.0000).In addition, the analysis of the logistic regression models showed that as private investment and urban planning increase local development increases, while as population density increases local development decreases (R = 81.2%).Furthermore, the more social services exist in a community such as help at home, shelter for elderly and there are more chances for employment then local sustainable development is increased In addition, as the number of homeless people increases local sustainable development decreases.(R = 80.2%).Also, Kruskal-Wallis H -tests were performed for the comparison of the four areas concerning demographical and residential elements as well as development elements, which showed that the opinion of the respondents from all four areas is similar as regards quality of life and job satisfaction at a = 1% signifi cance level.

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)0.000
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.043
GPT teacher head0.336
Teacher spread0.293 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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