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Record W7037426419

The Economic Impact of the UK Meeting & Event Industry

2013· report· en· W7037426419 on OpenAlexaboutno aff

Bibliographic record

VenueSurrey Research Insight Open Access (The University of Surrey) · 2013
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic impact analysisTourismConsistency (knowledge bases)Metropolitan areaEconomic dataInternational comparisonsImpact assessmentEconomic sectorEconomic evaluation
DOInot available

Abstract

fetched live from OpenAlex

The UK Economic Impact Study (UKEIS), commissioned by the Meeting Professionals International (MPI) Foundation and undertaken by Leeds Metropolitan University, represents a landmark study for the UK meeting industry. It is, to date, the most comprehensive assessment of the economic impact of the industry on the British economy. Although there has been growing recognition that the meeting industry makes a substantial economic contribution, the evidence base to support such a claim has, until now, been fragmented. Several valuable studies have been undertaken in recent years that have incorporated elements of the meeting industry, but their approach to economic modelling and data gathering have varied significantly. The lack of consistency and alignment with international standards has also prevented comparison between the value of the industry in one country and another. More importantly, it has made it difficult for the representatives of the meeting industry to provide evidence of its significance effectively. In order to provide a comprehensive profile of the UK meeting industry and to measure its economic impact robustly, the UKEIS adopted a framework designed by the UN World Tourism Organisation (UNWTO) for measuring the sector’s economic importance.3 This framework has been used for similar studies of the meeting industry in the USA, Canada, Mexico, Australia and Denmark. One of its particular strengths is that it connects with official national accounting systems, specifically Tourism Satellite Accounts.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0100.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.283
GPT teacher head0.429
Teacher spread0.146 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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