The Location of Canada's Immigrants and the Spatial Distribution of Canada's Overseas Visitors *
Bibliographic record
Abstract
Location of Canada's Immigrants and the Spatial Distribution of Canada's Overseas Visitors. The link between the locational choices of Canada's overseas visitors and the spatial distribution of Canada's immigrant populations is studied by combining information from Canada's International Travel Survey and the Canadian census. Visitors are influenced by the relative population size of a location and by the spatial distribution of their immigrant country-folk. The concentration of immigrants in a particular location does not have any explanatory power once the other two factors are taken into account. These conclusions apply to all types of traveller: vacationers; visitors of family and friends; students and workers. [much less than] The Location of Canada's Immigrants and the Spatial Distribution of Canada's Overseas Visitors [much greater than] [La localisation des immigrants au Canada et la repartition des visiteurs d'outre mer au Canada]. Cet article examine le lien entre les destinations des voyageurs internationaux au Canada (ceux des Etats-Unis sont exclus) et les destinations choisies par les immigrants au Canada. L'etude est base sur l'Enquete sur les Voyages Internationaux et le Recensement du Canada (tous les deux sont publies par Statistique Canada). Nous avons trouve que les voyageurs d'un pays particulier sont attires aux endroits ou se sont installes les immigrants du meme pays, et qu'ils sont aussi attires aux localits avec des concentrations de population plus grandes. Mais, selon noise etude, la proportion des immigrants dans la population d'une localite n'a pas d'influence sur le nombre de visiteurs. Ces conclusions s'appliquent a toutes les categories de visiteurs : ceux qui viennent pour prendre des vacances; ceux qui visitent leur famille ou leurs amis; ceux qui viennent pour etudier; et ceux qui sont en voyage d'affaires. ********** Canada receives over 17 million foreign visitors a year. Approximately three quarters of these come from the United States. Nevertheless, overseas visitors to Canada have a significant impact on Canada's economy. For example, in 1996 4.4 million overseas visitors arrived in Canada and collectively spent approximately 4 billion dollars. Moreover, the number of arrivals from overseas is growing much faster than arrivals from the United States. Between 1988 and 1996 overseas arrivals grew 55 % while arrivals from the United States grew just 5 % (Table 1). Given the importance of tourism not only in Canada but around the world, it is not surprising that there is a substantial literature devoted to analysing the demand for tourism services. Crouch (1994) presents a survey of that literature-he identifies the key variables and summarises, for example, income and price elasticity estimates. According to Crouch, a review of the literature reveals that income is the single most important explanatory variable in demand. However, elasticity estimates vary a great deal, but generally exceed unity and lie below 2.0, confirming that is a luxury good. As for price effects, Crouch argues that 'economic theory ensures that price must be included in any demand study, but in the study of tourism, the issue of price is particularly vexatious. The fundamental problem seems to be that international travel is a complex mix of goods and services for which no single price index is wholly adequate. Abstracting from these complexities, theory suggests that the real exchange rate should be an important factor in the demand for travel. Many studies have separated the nominal exchange rate effects from local price effects and this is the focus of work by Vilasuso and Menz (1998) who argue that when travellers are making plans they may be more aware of exchange rates than local prices in the destination country. Since the degree of uncertainty differs between the three components of the real exchange rate, Vilasuso and Menz argue that unequal weights are attached to these pieces of information. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".