ON THE PREVALENCE AND IMPACT OF VAGUE QUANTIFIERS IN THE ADVERTISING OF CAUSE-RELATED MARKETING (CRM)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A series of three studies examines potential consumer confusion associated with the advertising copy used to describe cause-related marketing (CRM) campaigns, where money is donated to a charity each time a consumer makes a purchase. The first study assesses the relative frequency of various copy formats in CRM on the Internet. The authors find that the majority of the copy formats (69.9%) are abstract (e.g., a portion of the proceeds will be donated), 25.6% are estimable (e.g., X% of the profits will be donated), and 4.5% are calculable (e.g., X% of the price will be donated). Subsequent studies find that (1) slight variations in abstract wording in advertising copy leads to considerable differences in consumers' estimates of the amount being donated, (2) the amount of the donation estimate for each abstract copy format varies considerably across individuals, and (3) the donation amount can impact choice. Taken together, the three studies demonstrate that the vast majority of advertising copy used to describe CRM donations is abstract, that different but legally equivalent abstract copy formats result in large differences in mean perceived donation level, and that these donation levels can impact consumer choice. Implications for advertising strategy and public policy are discussed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it