Bibliographic record
Abstract
This research aims to study the effects of oil price changes on the Colombian economy during 2001:Q1 to 2016:Q2. A structural vector auto-regression model in the spirit of Blanchard and Galí (2010) is estimated under a recursive identification scheme, where unexpected oil price variations are exogenous relative to the contemporaneous values of the remaining variables. Drawing on impulse-response estimates, a 10% increase in the oil price generates the following accumulated orthogonalized responses: i) a contemporaneous 0.4% increase in GDP growth, later on the effect reaches its maximum in the first quarter (1.7% increase) and starts to decay after two quarters; ii) a contemporaneous 1.2% decrease in unemployment, then the effect remains slightly negative and reaches its maximum after ten quarters (5.1% decrease); iii) a contemporaneous 0.9% decrease in inflation, followed by an 0.2% increase by quarter three, and thereafter the effect remains slightly negative
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".