Bibliographic record
Abstract
I am honoured to be included in this wonderful event celebrating Chuck Freedman’s career and very pleased to be discussing Pierre Fortin’s thoughtful paper on the Phillips curve in Canada. The short version of my discussion is: Chuck is amazing, Phillips curve research is important, and I thoroughly enjoyed the paper. Let me start with a few words about Chuck before I turn to the lessons from three decades of Phillips curve research and offer a few specific comments on Pierre’s paper. Like so many generations of economists at the Bank, I began one of my first research assignments by reading something Chuck had written many years earlier. I remember being impressed by its thoughtful marriage of wellarticulated economic theory with a healthy respect for the facts about the Canadian economy—something that is always harder than it sounds. But what has impressed me even more than his early papers is that Chuck has stayed at the forefront of the literature and has continued to produce insightful papers on a wide range of topics at an extraordinary pace
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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.357 | 0.156 |
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".