MétaCan
Menu
Back to cohort
Record W2060228568 · doi:10.5539/ibr.v8n3p133

The Review of Human Resource Strategies Applying in Hospitality Industry in South California

2015· article· en· W2060228568 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHospitality and Tourism Education
Canadian institutionsnot available
Fundersnot available
KeywordsHospitalitySalaryHospitality industryCruiseRentingBusinessWageMarketingGlobalizationHuman resourcesHuman resource managementEconomic shortageIndustrial organizationLabour economicsEconomicsManagementTourismMarket economyEngineeringGeographyGovernment (linguistics)

Abstract

fetched live from OpenAlex

Globalization and interactions through boarders is the major contributor to widespread improvement in many sectors across the economy and has given rise to new innovations incorporated talent with clients. This has led to a significant improvement in the hospitality sector as one of these economic strongholds incorporated with talent management as the backbone given the number of qualified personnel in the sector. The hospitality sector is inclusive of a number of interrelated businesses components such as–airlines, cruise lines, lodging properties, restaurants, car rental firms, tour operators and travel agents, among others. It is in dynamic growth and keeps diversifying to curb the customer needs which are ever changing (Hanson, 2013). There is a projection that wage and salary jobs will increase by 17% over the coming year 2014, a projection by the U.S Bureau of Labor and statistics, this is evidence of the fast rate of growth in the sector.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.108
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.387
Teacher spread0.284 · 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