BRIEFING PAPER TO THE ECONOMIC AND MONETARY COMMITTEE OF THE EUROPEAN PARLIAMENT FIRST QUARTER 2005
Bibliographic record
Abstract
1) The Euro Area is highly vulnerable to oil price shocks The world economy is vulnerable to oil price shocks and so it is that of the Euro Area. In principle, a country vulnerability to energy prices depends on its total volume of net oil imports as a percentage of GDP and of its total oil consumption as a percentage of GDP. The higher its ratio of net oil imports to GDP the higher will be the deterioration of its trade and current account balance and the more adverse will turn its terms of trade. This first effect tends to have a negative impact on the supply side of the economy by increasing the cost of the production of goods and services due to the increase of the relative price of the energy inputs, thus, reducing the profit margins of firms and their investment flows and employment rates. The higher the ratio of oil consumption to GDP, the higher will be its negative impact will be on the Consumer Price Index, reducing the purchasing power of consumers and their disposable income therefore, reducing overall consumption demand. Given a budget constraint, as the oil consumption demand is far more rigid, mainly in transport services, the reduction of consumption affects other goods and services which are considered by the consumer to be less superior. The magnitude of this second effect will depend on the degree of monetary response
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.021 | 0.010 |
| Insufficient payload (model declined to judge) | 0.095 | 0.056 |
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".