Mazatlán: The Destination That Did Not Like Its Brand
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
In 2022, Mazatlán was enjoying a reputation as a popular seaside town on the Mexican Pacific Coast, in the northwestern state of Sinaloa. Protected by a bay and three islands, it offered sandy beaches and favourable weather year-round, making it an attractive destination for Mexican, American, and Canadian vacationers. It was a popular stop for Pacific Ocean cruises, where tourists could enjoy beaches, sunshine, Mexican cuisine and culture, and various sporting activities including baseball, marathons, triathlons, sport fishing, and soccer. However, Mazatlán’s image was being tainted by unfavourable events, which presented unique challenges for the city’s marketers and threatened to endanger the city’s highly successful tourism industry. Mazatlán’s tourism authorities were wondering how to keep the city’s tourism brand and image strong, despite these new and significant challenges.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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