The Evolution of Product Placements in Hollywood Cinema
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
Abstract This content analysis of the 15 top-grossing motion pictures of 1977, 1987, and 1997 uncovered 546 product placements present in fully one quarter (24%) of the total running time of the 45 movies. Product leaders were automobiles (21% of all placements), beer (14%), and soda (11%), with Coca-Cola the overall brand leader. Full-display appearances remained dominant throughout. Most appearances were brief; however, “key” placements-lengthier showcases featuring brands in central heroic roles and in idealized images resembling TV commercials-increased over the 20-year period. Other related notable changes were increases in high-involvement placements (89%), implied endorsement placements (83%) (coupled with a 9% rise in “verbal/hands mentions,” the most valued placement), and “mentioned” placements (75%) (similarly coupled with a 9% rise in “used” placements), and the number of brands placed (32%) along with decreases in liquor placements (60%), association with minor characters (40%) and non-stars (36%), and both “signage” (24%) and “clutter” (20%) placements, the least valued.
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 | 0.001 | 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 | 0.000 | 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