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Record W4376573330 · doi:10.1111/fcsr.12483

Editorial for special issue

2023· article· en· W4376573330 on OpenAlexaboutno aff

Bibliographic record

VenueFamily and Consumer Sciences Research Journal · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsCitationComputer scienceLibrary scienceWorld Wide WebInformation retrieval

Abstract

fetched live from OpenAlex

The Family and Consumer Sciences Research Journal (FCSRJ) aims to present original research works in all areas of family and consumer sciences concerned with the well-being of individuals and families.The current special issue, titled "Consuming in Hospitality and Tourism during Pre-and Post-Pandemic," seeks to address the hospitality industry that has been severely impacted during the COVID-19 pandemic.As the pandemic subsides and travel restrictions ease, the hospitality industry needs to comprehend the industry challenges and customers' behavioral changes during and after the COVID-19 pandemic periods.The publication includes four research articles and one book review.All four research articles were conducted in different countries: Canada, Thailand, Portugal, and the USA.The reviewed book discusses post-pandemic hotel revenue management and strategies.The first article, titled "Canadians' Travel Knowledge Acquisition During the Pandemic: A Cognitive Mediation Model Approach," written by Shuyue

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.228
Threshold uncertainty score0.762

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.2280.125

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 head0.102
GPT teacher head0.371
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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