Would it be possible for every Canadian to own a polar bear
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 discusses the common stereotype/fantasy that every Canadian owns and rides a polar bear and whether this would be possible in real life. The paper begins with a background on polar bear range and eating habits, and then goes on to discuss sources of food in Canada. It was assumed only everyone of driving age would own a polar bear, allowing a population of 2.99x10 7 polar bears. It would take either 9.02x10 5 cows, 2.3x10 6 hogs, or 7.4x10 8 chickens per day to feed that amount of bears. Using cows and chickens as the model animals, the amount of pasture needed to support that much food for a year is calculated to be 4.5x10 7 km 2 for cows, which is larger than the total landmass of Canada, and 2.7x10 8 km 2 for chickens. While the landmass of Canada could support the chickens, due to their waste and pollution, it is concluded that it would not be possible for every Canadian to own a polar bear.
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 | 0.002 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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