Bibliographic record
Abstract
One of the most striking economic phenomena of recent decades has been the sharp disparity of growth rates across Organisation for Econ-omic Co-operation and Development (OECD) countries. The conse-quences of this disparity, in terms of differing performances in employment and prosperity, have been a cause of concern both for politicians and for citizens. Added to this is a concern about how the fruits of economic growth are allocated within and between present and future generations. There have been worrying signs of growing income inequality, exclusion of particular groups and indications of increased social dysfunction. The intertemporal and intergenerational equity aspects of economic growth are of growing importance given demographic and social pressures. Access to learning throughout life as well as active participation in the labour market remain important conditions for social cohesion and the maintenance of consensus on the reforms required to underpin sustained growth and well-being. In sum, recent developments pose a challenge to governments and civil society in general. In this context, and responding to a mandate from Ministers meet-ing in the Council of the OECD in May 1999, the OECD Secretariat initiated a program of work to identify some of the factors that influ-ence growth, as well as policies that could strengthen overall econom-ic performance. Ministers asked the OECD to study the causes of growth disparities, and identify factors and policies which could strengthen long-term growth performance. These include areas such as rapid technological innovations and the growing impact of the knowledge society and its demand on human capital. The program of work initiated seeks to address a broad set of questions and issues related not only to the factors influencing economic growth, but to how learning, networks and civic traditions contribute to a variety of economic and social outcomes and how these outcomes need to be bal-anced to achieve sustainable economic and social development. In Canada, the Policy Research Initiative (PRI) of the federal govern-ment produced a report in 1999 entitled Sustaining Growth, Human
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.594 | 0.422 |
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".