A Tale of Two Studies: Replicating ‘Advertising Effectiveness and Content Evaluation in Print and on the Web’
Bibliographic record
Abstract
ABSTRACT We replicate, using adult web users, a study comparing advertising effectiveness and content evaluation in print and on the web (Gallagher, Foster, and Parsons, 2000). As in the original study involving students, the replication found that advertising was equally effective in the two media. However, while the original study found that evaluation of an article containing advertising was lower when it appeared on the web than when it appeared in print, this result was not replicated. Examination of two subgroups showed that results for the subgroup resembling the student sample were consistent with the original study. We propose conditions under which student samples are appropriate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.271 | 0.475 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".