449 - Where Is Inflation Going & What Does It Mean For You? w/ David Macdonald
Bibliographic record
Abstract
We are no strangers to inflation, with the cost of living soaring to new records. But what's really causing inflation? Where are our dollars going and what's the impact on the economy? On today's podcast, David Macdonald, a senior economist at the Canadian Centre for Policy Alternatives, returns to discuss his research on why we see inflation and who benefits. David also shares his thoughts on employment, where wages are headed, and whether credit card debt will continue to trend upwards. Tune in for a very informative discussion!Related Links:Podcast 319: CERB Transition to EI https://youtu.be/piEhsYgWU8IPodcast 114: Basic Income, Is it a Silver Bullet for Poverty? https://youtu.be/mi3tWjg1bC4Where Are Your Inflation Dollars Going Report: https://policyalternatives.ca/publications/reports/where-are-your-inflation-dollars-goingDavid Macdonald on Twitter: https://twitter.com/DavidMacCdnCanadian Centre for Policy Alternatives: https://policyalternatives.ca/ Episode 435 December 31, 2022, Year-End Predictions show, https://youtu.be/3i22JpmcozY Statistics Canada Consumer Price Index Portal: https://www.statcan.gc.ca/en/subjects-start/prices_and_price_indexes/consumer_price_indexesStatistics Canada. Table 18-10-0004-01 Consumer Price Index, monthly, not seasonally adjusted https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810000401 Time Stamps:1:34 What is Inflation and Where Is It Going5:10 Who Benefits From Inflation?12:42 Wages vs. Inflation16:27 Is Unemployment Actually Low?18:48 Why We Didn't Have the Great Resignation in Canada24:30 Is Now the Best Time To Change Jobs?27:10 Will Credit Card Debt Keep Going Up?
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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) | 0.051 | 0.012 |
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".