Changing Demands on Economic Research: The Austrian Institute of Economic Research Since 1980
Bibliographic record
Abstract
Over the years, the Austrian Institute of Economic Research has been called upon to respond to a constantly changing brief. After 1980, the economic policy system had to be adapted to a newly opened macroeconomy and the liberalisation of international capital markets. The rising complexity of issues required better statistical underpinnings, large-scale databases, computers, new analytical and forecasting methods, increasingly complex models. Ageing, globalisation and competition at different cost structures emerged as major issues. In all these projects, WIFO is bestirring itself to achieve innovative solutions, with the result that it is frequently very much at the cutting edge of the international discourse. Staff numbers have been greatly enlarged and internationalisation is pushed forward; international contracts now make up a quarter of all of WIFO's work.
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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 | 0.054 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.015 | 0.023 |
| Insufficient payload (model declined to judge) | 0.014 | 0.017 |
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".