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UNWTO World Tourism Barometer and Statistical Annex, May 2019

2019· article· en· W4256340920 on OpenAlexaboutno aff

Bibliographic record

VenueUNWTO World Tourism Barometer · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTourismQuarter (Canadian coin)EarningsBarometerIndex (typography)GeographyAnnual growth %Agricultural economicsBusinessEconomicsEconomyFinance

Abstract

fetched live from OpenAlex

International arrivals grew 4% in the first quarter of 2019 International tourist arrivals (overnight visitors) grew 4% in January-March 2019 compared to the same period last year, below the 6% average growth of the past two years. Growth was led by the Middle East (+8%) and Asia and the Pacific (+6%). Europe and Africa (both +4%) and the Americas (+3%) also recorded an increase in arrivals in this first quarter of 2019. Confidence in global tourism performance has started to pick up again after slowing down at the end of 2018, according to the latest UNWTO Confidence Index survey. The Panel’s outlook for the current May-August period is more optimistic than in the past three periods and more than half of respondents are expecting a better performance in the coming four months. Total exports from international tourism reach USD 1.7 trillion in 2018 Total export earnings from international tourism reached USD 1.7 trillion in 2018, or almost USD 5 billion a day on average. International tourism (travel and passenger transport) accounts for 29% of the world’s services exports and 7% of overall exports of goods and services. For the seventh year in a row, growth in tourism exports (+4%) was higher than growth in merchandise exports (+3%) in 2018.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.015
GPT teacher head0.294
Teacher spread0.279 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations20
Published2019
Admission routes1
Has abstractyes

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