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Record W2320607729 · doi:10.1177/1096348015584437

Virtual and Hybrid Meetings: A Mixed Research Synthesis of 2002-2012 Research

2015· article· en· W2320607729 on OpenAlexaff
Carole B. Sox, Sheryl F. Kline, Tena B. Crews, Sandra K. Strick, Jeffrey M. Campbell

Bibliographic record

VenueJournal of Hospitality & Tourism Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsColumbia College
Fundersnot available
KeywordsHospitalityTourismHospitality management studiesTheme (computing)Hospitality industryFace (sociological concept)SociologyPublic relationsMarketingKnowledge managementPsychologyComputer scienceWorld Wide WebBusinessPolitical scienceSocial science

Abstract

fetched live from OpenAlex

This research presents an examination of literature written within hospitality and tourism studies and within other disciplines pertaining to virtual and hybrid meeting genres over a 10-year period (2002-2012). While 15 articles were found within hospitality and tourism journals, 67 articles were included within this review, with the majority published within refereed journals outside of hospitality and tourism. Articles were categorized by journal, year, methodology, and theme. Using the diffusion of innovation theory, five themes emerged: comparison of virtual and/or hybrid meetings with face-to-face meetings, perceptions and attitudes toward virtual and hybrid meetings, management and design of virtual and/or hybrid meetings, specific audiences for virtual and hybrid meetings, and uses of technology within virtual and hybrid meetings. These articles have been accumulated to identify gaps in the literature and provide future research recommendations within hospitality and tourism to be addressed.

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)0.014
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.022
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.001
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 head0.222
GPT teacher head0.458
Teacher spread0.235 · 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 designQualitative
Domainnot available
GenreReview

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

Citations36
Published2015
Admission routes1
Has abstractyes

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