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Record W2106531460 · doi:10.1504/ijemr.2010.036884

Marketing in a Web 2.0 world with a Web 1.0 mentality: the challenge of social web marketing in academic institutions

2010· article· en· W2106531460 on OpenAlexaff
Lyle Wetsch, Kristen Pike

Bibliographic record

VenueInternational Journal of Electronic Marketing and Retailing · 2010
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPaceThe InternetMarketingWeb engineeringWorld Wide WebDigital marketingBusinessWeb designWeb developmentComputer scienceWeb intelligence

Abstract

fetched live from OpenAlex

The internet has changed the way people live, work and communicate in a very short period of time. It was not that long ago that e-mail was considered the 'new wave' of communication (Wilkes, 1990) and the possibility of near instantaneous communication resulted in previous communication technologies being referred to as 'snail mail' due to its antiquated pace. While e-mail was originally adopted by the young, technically savvy generations, now older generations have followed suit. This pattern is consistent with each new wave of technology that enters the market. Many companies are content to offer their static web pages out to the general public, but the emerging generations are being raised on a more interactive and dynamic Web 2.0 world. In order to market effectively to these emerging generations, businesses and managers are forced to evaluate and adopt emerging technologies at a greater pace. This paper addresses the challenges that academic institutions face when moving to a Web 2.0 marketing concept when legacy thinking (Web 1.0) still resides in the organisation.

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)0.011
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.037
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.030
Scholarly communication0.0370.030
Open science0.0010.007
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0060.002

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 head0.013
GPT teacher head0.271
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 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

Citations2
Published2010
Admission routes1
Has abstractyes

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