Covid's Impact on Jobs, IPSOS Poll on Summer Outlook, Local Community & Covid and Storybook Theatre's "Smartest Girl In The World"
Bibliographic record
Abstract
Welcome to the \\"Mornings with Sue & Andy\\" podcast for Thursday, May 20th.We begin with a look at the massive impact the COVID-19 Pandemic has had on jobs in Canada. We hear details on a new study that suggests now is the time to roll out a national plan with a strong focus on 'targeted training'.How are Canadians feeling about the upcoming summer? From festivals, to travel and even indoor gatherings we get details on a new IPSOS poll which digs-in to the topic. They are staples in many communities around Calgary, but many may have to close their doors, another victim of the COVID pandemic. We'll look at the state of local Community Associations - and what can be done to keep them afloat.And finally, it's a family-friendly way to keep the gang entertained through a rainy long weekend! We hear all about Storybook Theatre's final 'virtual show' of the season: \\"The Smartest Girl in the World\\".
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.260 | 0.054 |
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".