What is it like to be a Canadian by choice? Why is Canada appealing to newcomers? And more on our nation and the 150th anniversary of confederation
Bibliographic record
Abstract
The Roy Green Show Podcast This is Roy Green's story about arriving in Canada as a 'reluctant' 13-year-old to becoming a 100% very proudly self-identified Canadian. -Following Iranian revolution in 1979, Marina was arrested at 16 years of age and spent two years in the notorious Evin political prison in Tehran where she was tortured and came very close to being executed.Eventually released, Marina came to Canada in 1991 and wrote her memoir, Prisoner of Tehran. In 2007 Marina received the inaugural Human Dignity Award from the European Parliament. In '09 she wrote her second book, After Tehran: A Life Reclaimed. What is it like to be a Canadian by choice? Guest: Marina Nemat, Born in Tehran, Iran-Immigration is a constant issue in Canadian debate. What makes Canada appealing to newcomers? What countries were you considering applying to as an immigrant and what made you decide to choose Canada? Also; do multi-generational Canadians support immigration numbers at 300,000 annually and are newcomers making a real effort to assimilate into Canada?Guest: Mario Canseco, Immigrant from Mexico and vice president of Insights West polling firm.-A year ago the massive wildfire which caused an evacuation and destruction of much of Fort McMurray resulted in Canadians donating $50 million through the Red Cross to their fellow Canadians from the Alberta community. Guests: Stacy and Kevin, Fort Mac residents and evacuees.-Reflections of Canada: Illuminating our Opportunities and Challenges at 150 years. A book published by the Peter Wall Institute for Advanced Thinking at the University of British Columbia. It contains 41 essays by some of Canada's most critical thinkers of the nation in which we live. The positive and the not so positive.Guests: Margot Young, Professor of law at UBC and co-editor of Reflections of Canada. Maxwell Cameron, Political science professor UBC.Learn more about your ad choices. Visit megaphone.fm/adchoices
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 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 teacher head, 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".