Travel Risks in a Time of Terror: Judgments and Choices
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
Shortly after the 2002 terrorist attacks in Bali, readers of Conde Nast Traveler magazine were surveyed regarding their views on the risks of travel to various destinations. Their risk estimates were highest for Israel, and lowest for Canada. Estimates for the different destinations correlated positively with (1) one another, (2) concern over aspects of travel that can make one feel at risk (e.g., sticking out as an American), (3) worries about other travel problems (e.g., contracting an infectious disease), and (4) attitudes toward risk. Respondents' willingness to travel to a destination was predicted well by whether their estimate of its risk was above or below their general threshold for the acceptability of travel risks. Overall, the responses suggest orderly choices, based on highly uncertain judgments of risks. Worry played a significant role in these choices, even after controlling for cognitive considerations, thereby supporting the recently proposed "risk as feelings" hypothesis. Thus, even among people who have generally consistent and defensible beliefs, emotions may affect choices. These results emerged with people selected for their interest in and experience with the decision domain (travel), but challenged to incorporate a new concern (terror).
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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