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Record W2725952321 · doi:10.5430/jms.v8n3p35

Assess the Application Level of Hotels Located in Aqaba City to the ENAT Standards from the Staff’s Point of View

2017· article· en· W2725952321 on OpenAlexvenueno aff
Ibrahim Bazazo, Mohammed Abdullah Nasseef, Omar Al-Nsour, Sara Altheeb, Hameed Abu Alez

Bibliographic record

VenueJournal of Management and Strategy · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
Fundersnot available
KeywordsToiletTourismBusinessWork (physics)MarketingPoint (geometry)Transport engineeringGeographyEngineering

Abstract

fetched live from OpenAlex

The aim of this research is to explore the degree to which Aqaba city hotels apply ENAT (European Network for Accessible Tourism) standards towards disabled tourists. These include physical accessibility/outside areas, physical accessibility/internal access routes, toilet and bathroom, staff and additional services, and equipment for accessible venues. A total of 142 questionnaire containing 32 items was used to collect information from employees work in three, four, and five star hotels. Results of the current study revealed that the researched hotels apply ENAT standards to a great extent except for equipment for accessible venues. This study shall provide important feedback to hoteliers’ decision-makers who are significant factors that can enhance the disability's services and put the hotel industry in Aqaba city at a competitive edge.

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)0.002
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.112
GPT teacher head0.301
Teacher spread0.189 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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