International Consumer Product Testing Across Cultures and Countries: Canada
Bibliographic record
Abstract
Canada is located in the northern half of North America, and covers a land mass of 9 97 610 km2. The southern Canadian border of 8892 km is shared with the United States. Much of the Canadian population is concentrated along this border. Canada is divided into ten provinces and three territories. There are six time zones across Canada. Newfoundland is 3 hours and 30 minutes behind Greenwich Mean Time (GMT). Other time zones are the Atlantic (4 hours behind GMT), Eastern (5 hours behind GMT),Central (6 hours behind GMT),Rocky Mountain (7 hours behindGMT) and the Pacific, 8 hours behind GMT. Canada is divided into several regions, each with a unique climate and landscape. The Pacific Coast has a moderate climate, with relatively dry summers and mild, wet winters. Other geographical areas of interest include the Rocky and Coastal mountain ranges, the plains of Alberta, Saskatchewan, and Manitoba, the rocky Canadian Shield region, and the cold Arctic region, north of the tree line. Only 12% of Canada’s land is suitable for agriculture. In general, summer temperatures in the milder regions can reach 35°C and higher, while winter temperatures of −25°C are not uncommon. Canada is essentially stable politically and is undergoing no internal civil conflicts. Canadians as a whole are considered more conservative than their American counterparts. The Canadian infrastructure is highly developed for communication and transportation. Canadian consumers are similar to other North American cultures (i.e., United States), but some cultural differences may affect research results. Canada recognizes two official languages, English and French. Of Canada’s 30 million people, 59 % declare English to be their mother tongue, 23 % state French as their first language and 18 % have more than one first language or their mother tongue is neither English nor French. More than two-fifths of Canadians have one origin other than British, French, or Aboriginal. Canadians take pride in their multiculturalism; Canada became the first country in the world to adopt a multiculturalism policy in 1971.
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.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.013 |
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".