Bibliographic record
Abstract
Human resources are recognised as being key to the creation, commercialisation and diffusion of innovation. Among them, doctorate holders are not only the most qualified in terms of educational attainment, but also those who are specifically trained to conduct research. In 2004, the OECD launched a collaborative project with the UNESCO Institute for Statistics and Eurostat aimed at developing internationally comparable indicators on the labour market, career path and mobility of doctorate holders. This Working Paper presents the second edition of the technical guidelines used in the framework of the Careers of Doctorate Holders (CDH) project. The technical guidelines are composed of: i) the methodological guidelines; ii) a core model questionnaire and instruction manual; and iii) the output tables used for reporting data at the international level and related definitions. This second edition builds on the experience resulting from the first large scale data collection, which was based on the first edition of the technical guidelines released in 2007. In addition to a number of basic adjustments, it proposes new ways to measure post-doctoral positions and types of mobility, including international mobility. The current draft is the result of discussions among the members of the CDH expert group. Its aim is to provide guidance to countries that wish to implement the project at national level.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".