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Record W985775454

A Strategic Analysis of Mobile Data Service Offerings for the Vancouver 2010 Winter Olympic Games

2008· article· en· W985775454 on OpenAlexfundaboutno aff
Benjamin YM Kwan

Bibliographic record

VenueSummit (Simon Fraser University) · 2008
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsService (business)BusinessAdvertisingComputer scienceMarketing
DOInot available

Abstract

fetched live from OpenAlex

This paper is a strategic analysis of the roles mobile services may play in the upcoming 2010 Winter Olympics and Paralympic Games in Vancouver, British Columbia. The paper has two objectives. First, the paper outlines the projected, infrastructure landscape that vancouver2010.com may operate in during the Games. The paper identifies trends in a mobile-communication technology mix and mobile-user demographics that drive consumer demand. This research identifies the driving forces that will shape the competition for projected market share in the 2010 mobile phone market. The paper can thus help the Vancouver Organizing Committee for the 2010 Olympic and Paralympic Winter Games(VANOC) identify the target segments for delivering value-added services in mobile communications. The second objective of this paper is to suggest a list of potential services, which will meet the goal of improving tourist ease of use in accessing mobile services while attending Olympic events. The paper utilizes extensive secondary market research to develop this list.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.113
GPT teacher head0.311
Teacher spread0.198 · 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
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

Citations1
Published2008
Admission routes2
Has abstractyes

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