Measuring Attitudes : Comparing Canadian and Finnish Attitudes toward Chinese Immigrants after COVID-19
Bibliographic record
Abstract
Aim: The aim of the study was to investigate Canadian and Finnish attitudes toward Chinese immigrants in their respective countries. Method: An online questionnaire was completed by 249 participants, 171 Canadians and 78 Finns. The data was analyzed in SPSS using two sample t-tests, factorial ANOVAs, and ANCOVAs. Results: The study showed that Canadians (M = 4.26) had significantly more positive attitudes toward Chinese immigrants than Finns (M = 3.6) when using the Bogardus Social Distance Scale. Similar results were found when measuring the topics of culture (Canada M = .44, Finland M = .2) and safety (Canada M = 1.03, Finland M = .94). The topic of employment and general attitudes had no significant difference. Gender, education, political beliefs and if participants personally knew someone Chinese were all found to have some effect on results. Conclusions: Overall, Canadian and Finnish attitudes toward Chinese immigrants tended to be quite similar, with Canadians having more positive attitudes than Finns in some areas. Further research is required to validate these findings within the field.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".