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Record W2338483434 · doi:10.2501/jar-41-4-57-70

The Medium Is Not the Message: Advertising Effectiveness and Content Evaluation in Print and on the Web

2001· article· en· W2338483434 on OpenAlexaff
Katherine Gallagher, K. Dale Foster, Jeffrey Parsons

Bibliographic record

VenueJournal of Advertising Research · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAdvertisingAssertionContextual advertisingNative advertisingOnline advertisingAdvertising researchComputer scienceWorld Wide WebBusinessThe Internet

Abstract

fetched live from OpenAlex

ABSTRACT Some have argued that traditional principles of mass media advertising do not apply on the web. We present an empirical study that contradicts this assertion. Our findings suggest that advertisers need not take full advantage of the enhanced capabilities of the medium to produce effective web advertising. Given equal opportunity for exposure to the target audience, the same advertisements were equally effective in print and on the web. However, for promotional material that consumers would not classify as advertising, evaluations were lower when the material was presented on the web. We propose a plausible explanation for this apparent paradox.

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)0.008
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0060.005
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.124
GPT teacher head0.425
Teacher spread0.300 · 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 designObservational
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

Citations175
Published2001
Admission routes1
Has abstractyes

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