C-Suite Unplugged: Alan Norris, Executive Chairman, Brookfield Properties
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
When given the chance to advance one's career by going to India, Bermuda, or Calgary, you may be surprised to hear someone chose the sunny Alberta city given the options. But after four kids, nine grandchildren, and a successful merger to create a North American powerhouse, there's nowhere Alan Norris would rather be.On this episode, we speak with Alan Norris, Executive Chair of Brookfield Properties, about his journey to the C-Suite, his experience taking an ailing company from the edge of bankruptcy into a successful merger, and the role of an Executive Chair.We also discuss housing affordability in Canada and North America, the importance of being present within the community, and the value of passion in one's career.------------About The Business Council of AlbertaThe Business Council of Alberta was founded on a simple idea: to make life better for all Albertans. We believe that business has an important role in improving society, and that when business does well, we all do well. We work with the chief executives and leading entrepreneurs of Alberta's largest enterprises to understand the big, long-term challenges that Albertans are facing and work with industry, government, and civil society to solve these problems and build shared prosperity for every person who calls Alberta home.Check out more of our recent work: https://bit.ly/3JG9ifSCheck out recent episodes of AlbertaBETTER: https://bit.ly/3bHlfFBSubscribe to our monthly newsletter: https://bit.ly/3BPxDhvFollow us on social media:Twitter: https://bit.ly/3P7pgB0Facebook: https://bit.ly/3Qx6B2JLinkedIn: https://bit.ly/3QaetHEYouTube: https://bit.ly/3QswqAV
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.151 | 0.029 |
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