Inflation vs. Retirement, Pandemic impact on Canadian youths, January 6th hearings, Wilder Institute conservation efforts
Bibliographic record
Abstract
We begin with a look at how both the Pandemic and record-high inflation rates are impacting the retirement plans of Canadians. We get some insight from David Gunn, President of Edward Jones Canada.Next, it's been a tough couple of years for all of us, and has certainly been hard on post-secondary students, many of which have been forced to 'pause' their schooling or push back their graduation. We hear details on a new study from the C.D. Howe Institute focusing on the topic and how it could ultimately affect Canada's labour market.Then, we head to South of the border to speak with Reggie Cecchini, Washington Correspondent for Global News. Reggie brings us the latest on the continuing hearings into the January 6th insurrection and former President Donald Trump's involvement on that historic day.Finally, it's our monthly conversation with Dr. Axel Moehrenschlager, Wilder Institute/Calgary Zoo's Director of Conservation and Science. This time out, Dr. Moehrenschlager shares the story of the global effort to re-introduce a very unique species of tree to Easter Island.
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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) | 0.137 | 0.002 |
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; both teacher heads agree on what is shown here.
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".