Bibliographic record
Abstract
Redistribution and marginal productivity reward / Alexander W. Cappelen, Bertil Tungodden -- Progressivity implications of public health insurance funding in Canada / James B. Davies, Michael Hoy -- Public and private health insurance and the utilisation of health care in Spain / Pilar García Gómez, Angel López Nicolás -- Aging and inter-generational fairness : a Canadian analysis / Michael Wolfson, Geoff Rowe -- Changing poverty or changing poverty aversion? / Daniel L. Millimet, Daniel Slottje, Peter J. Lambert -- A gender-focused macro-micro analysis of the poverty impacts of trade liberalization in South Africa / John Cockburn, Ismael Fofana, Bernard Decaluwe, Ramos Mabugu, Margaret Chitiga -- Inequality and income gaps / Ian Preston -- How progressive is progressive taxation? An axiomatic analysis / Udo Ebert, Georg Tillmann -- Generalized probabilistic egalitarianism / Paul D. Thistle -- Inequality and the choice of the personal tax base / Nigar Hashimzade, Gareth D. Myles -- Strategic weight within couples : a microsimulation approach / Kristian Orsini, Amedeo Spadaro -- Introduction / Peter J. Lambert
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.191 | 0.026 |
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".