Bibliographic record
Abstract
As digital-video-recorders (DVRs) become more popular, an increasing number of television commercials are being zipped (fast-forwarded). This paper examines how memory for brand names, products and attitudes toward commercials are influenced by zipping at the speeds used by the popular DVR manufacturer, TiVo (300, 1800 and 6000 percent). Experimental results show that compared to ads shown in real-time, memory for the advertised brand names improves when the commercials are zipped at 300 percent of normal speed. However, brand name recall dramatically declines as the commercials are zipped at faster speeds (1800 and 6000 percent). Speed of zipping had a significant effect on the ability to recall the advertised brand for all commercials except those at the end of a commercial pod. This suggests that all else being equal, ads placed at the end of a commercial pod are more likely to be recalled at all zipping speeds. Viewers of zipped commercials had more neutral attitudes toward the ads compared with those who saw them in real-time.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".