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Record W2073794093 · doi:10.1016/j.sbspro.2011.09.070

Tourism Sector in Order to Recovering From the Recession: Comparison Analyses for Turkey

2011· article· en· W2073794093 on OpenAlexaboutno aff
Mehmet Sarıışık, Didar Sarı, Selahattin Sarı, Muhsin Halis

Bibliographic record

VenueProcedia - Social and Behavioral Sciences · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismRecessionRevenueCompetitor analysisBusinessTreasuryOrder (exchange)Global recessionQuarter (Canadian coin)Christian ministryFinancial crisisEconomic sectorEconomic policyEconomicsFinanceEconomyMarketingGeographyMacroeconomicsPolitical science

Abstract

fetched live from OpenAlex

2008 economic crisis hit very hard many sectors globally, beside tourism, too. According to the economical and financial reports, the demand of hotel & restaurant industry declined sharply, and as a result of that situation tourism revenues had been affected negatively. Turkey was one of the few destination, which had a growing at the international tourist arrivals despite the 2008 crisis. Although the tourism revenues declined, but it was little while comparing with its competitors. Via the analyses of data's has been obtained by Prime Ministry Undersecretaries of Treasury, the effects of the main sectors operating in Turkey and their ratios on GDP during recession periods has been compared. As a result of those reports, tourism industry (hotels & restaurants) has been attracting attention with a quick recovering, by the last quarter of 2008. It can be said that tourism has been also main industry during recession periods with generating revenues and helping for current payments deficits

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
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 head0.514
GPT teacher head0.515
Teacher spread0.001 · 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 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

Citations16
Published2011
Admission routes1
Has abstractyes

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