Le débat sur la croissance économique en Suisse Quelles conclusions ? (text in French)
Bibliographic record
Abstract
" Switzerland is the growth laggard in the industrial world " - this dismal view has become part and parcel of today's conventional wisdom in Switzerland and elsewhere. We show it to be but partially true : accurate when judged by the trend growth rate of officially recorded real GDPs in 1970-2003, but not when considering what we call "adjusted real gross national incomes" ; i.e. a better measure of the populations' material wellbeing than real GDPs, although less correlated with employment and unemployment. The adjustment has to do with how to deflate the balance of goods and services as well as the balance of factor income. More important, and perhaps novel, is that there appears to be no statistically significant difference between the estimated trend growth rate of Switzerland's corrected gross national income and that of most other European countries : almost all tend to grow at a rate of about 2% p.a. There is however a significant long-term growth differential between these European countries, including Switzerland, and overseas ones such as Australia, Canada and the USA. This is because most of Europe suffers from well-known and weighty structural problems, not necessarily the same everywhere, but which should be addressed urgently and efficiently everywhere. The paper also includes a "parable" on the economic impact of oil price shocks, which may be useful for didactical purposes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.044 | 0.012 |
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".