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Record W3215954746 · doi:10.7202/1075090ar

A Prototype Executive Information System For The Ski Industry

2021· article· en· W3215954746 on OpenAlexaffabout
Karim B. Dossa, Peter W. Williams

Bibliographic record

VenueTéoros Revue de recherche en tourisme · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTourismExecutive information systemOrder (exchange)BusinessMarketingProduct (mathematics)Business intelligenceIconComputer scienceInformation systemDecision support systemKnowledge managementProcess managementManagement information systemsEngineeringData mining

Abstract

fetched live from OpenAlex

In few other areas of activity are the generation, gathering, processing, application and communication of information as important for business as they are in the travel and tourism industry. Ski area executives need to understand their markets in order to effectively interact with them. For this, managers have to be able to generate enough timely information about the market to support their decision making processes. This study develops a prototype ski executive information system for the Canadian ski industry. It is designed to provide ski industry executives with a readily accessible source of product and marketing intelligence to assist in strategic decision making. The icon and menu based grapical interfaces developed in this prototype combine to provide a user friendly information retrieval system whose efficiencies could eventually provide a botter use of various tourism data bases by decision makers.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.024
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0200.005

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 head0.128
GPT teacher head0.386
Teacher spread0.258 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2021
Admission routes2
Has abstractyes

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