Bibliographic record
Abstract
figurEs 1.1 Gini coefficient for fifteen OECD countries, 2017 or latest year / 8 1.2 Total tax revenues as a percentage of GDP, fifteen OECD countries, 2016 / 10 1.3 Total tax revenues as a percentage of GDP, Canada and three groups of countries, 1965-2017 / 10 2.1 The relative frequency of the word "neighbourhood" in the Globe and Mail, 1900-2009 / 35 2.2 The geography of Toronto's slums, 1944 / 37 2.3 Share of annual market income earned by the top 1%, Canada and United States, 1920-2015 / 41 2.4 Immigrant population in Canada, 1871-2016, and projection to 2036 / 42 2.5 The growth of urban homeownership, 1901-2011 / 48 3.1 Census tract typological transition matrix, joint CMA and time analysis / 66 4.1 Occupational income polarization in the Toronto CMA / 83 4.2 Relative incomes of visible minorities and recent immigrants, Toronto CMA / 83
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.740 | 0.548 |
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; the direct Gemma label and the distilled Codex classifier 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".