How Well Do You Know Your Neighbor? College Knowledge: Canada vs The United States
Bibliographic record
Abstract
abstract: As the world becomes more globalized, the role of geographic knowledge in everyday affairs grows. Notwithstanding this idea, previous research surveys indicate that young adults are geographically illiterate but little research has been done in the past decade to investigate if this still holds true. In order to examine the current geographic literacy of young adults, American and Canadian college students were surveyed regarding geographic knowledge of their neighboring country. To do this, I made a trip to the University of British Columbia in Vancouver, British Columbia to survey Canadian students in person. I also did in person surveys at Arizona State University to collect American students' knowledge. Both surveys were done with pen and paper and questions were either identical or similar in what geographic knowledge the question was testing the survey taker on (i.e what is the capital of Canada for American students and what is the Capital of the United States for Canadian students). Results indicated that despite being from different countries, both participant pools showed similar knowledge about their neighboring country with almost identical scores; American college students answered an average of 50% of the questions correct and Canadian students slightly above that at 51% of questions correct. Although the scores were similar, underneath the overall survey results was a lot of variety in the students' responses, particularly regarding the subject and questions each student pool excelled in. In conclusion, however, it seems that both Canadian students and American students struggled more with political geography than they did with cultural geography but are overall illiterate in geographical knowledge with only being able to answer half of the questions correct.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".