Green Shirt Day, Mercedes Stephenson, Sandip Lalli, Alberta Hotels, Dealing With Boredom, Working From Home
Bibliographic record
Abstract
Welcome to The Morning News Podcast for Tuesday, April 7th.Green Shirt Day aims to raise awareness about organ donation and encourage more people to register as donors. The day honours the memory of Humboldt Broncos bus crash victim, Logan Boulet. Sue and Andrew speak with Logan's father, Toby Boulet.The Morning News is joined by Mercedes Stephenson, Global's Ottawa Bureau Chief and Host of \\"The West Block\\". Mercedes gives Sue and Andrew an update on how the Canada Emergency Response Benefit roll-out is working into day 2 of the program.Sue and Andrew look at the impact the Coronavirus Crisis is having on local businesses. Sandip Lalli, President and CEO of the Calgary Chamber of Commerce, has the latest information, including how the Chamber is adapting during this time.The hotel industry has been hit very hard by COVID-19. The Morning News hears from the President of Alberta's Hotel and Lodging Association about the state of business.It's a fact of life these days in isolation are leaving people feeling bored. Sue and Andrew catch up with a psychologist who breaks down what boredom means and why it may not be such a bad thing after all.Finally - working from home can be a welcomed change for many, but it can also be a 'pain in the neck' for others. Sue and Andrew chat with an ergonomics professional on how to keep healthy in the home office.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.218 | 0.003 |
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".