Indigenous Experience & Pandemics (Part 1)
Bibliographic record
Abstract
This first episode introduces the history of pandemics and their impact on First Nation lives, communities, jurisdictions, and trajectories. First Nations Tax Commission (FNTC) Chief Commissioner C.T. Manny Jules discusses this history and his vision for change. Chief Commissioner Jules has dedicated over 40 years of his life to public service in support of First Nations. He is a member of Tkemlups te Secwepemc and served as Chief for over 16 years. He was the driving force behind the First Nations Fiscal Management Act, passed by Parliament in 2005, creating the First Nations Tax Commission, where he currently serves as Chief Commissioner.This episode was recorded on June 3, 2020. SHOW NOTES: First Nations Tax Commission: www.fntc.ca The mission of the FNTC is to help First Nation governments build and maintain fair and efficient property tax regimes and to ensure those First Nation communities, and their taxpayers alike, receive the maximum benefit from those systems.The FNTC is also about creating the legal, administrative and infrastructural framework necessary for markets to work on First Nation lands, creating a competitive First Nation investment climate, and using economic growth as the catalyst for greater First Nation self-reliance.Fiscal Realities: http://www.fiscalrealities.com/ Fiscal Realities Economists conducts economic research and analysis, develops innovative solutions, and advises and advocates for public, First Nation and private sector clients.Tulo Centre of Indigenous Economics: www.tulo.ca The Tulo Centre is a Canadian charitable organization dedicated to renewing Indigenous economics by providing applied programs to enhance the capacity of Indigenous communities. Book Recommendation: The Great Influenza: The Story of the Deadliest Pandemic in History. Written by John M. Barry: https://www.penguinrandomhouse.ca/books/288950/the-great-influenza-by-john-m-barry/9780143036494 ____Intro and outro song: John Jules Cover art work: Chief Commissioner Jules
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) | 0.194 | 0.010 |
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".