Psychological factors of Canadian and Mexican tourists and the US tourism sector
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
This paper investigates the impact of psychological factors of Canadian and Mexican tourists on the US tourism sector. Using the data of 1996–2019, the study uses vector autoregression models and the spillover analysis to perform the investigation. The paper discovers that high insecurity of tourists significantly reduces tourist arrivals, passenger fare receipts, and expenditure of tourists in the US. Also, tourist inflows are highly influenced by insecurity during terrorist attacks, natural disasters, and the financial crisis of the US. It is found that high sentiment of Canadian and Mexican tourists increases their outbound travel to the US, but the impact of sentiment is relatively stronger for the Canadian tourists. Results show that the tourist inflows from Canada and Mexico are influenced by low sentiment during recessionary periods of Canada and Mexico, respectively. The paper finds no robust evidence of mood and nationalism-based retaliation of tourists for traveling to the US.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it