Statistics on Income and Living Conditions (SILC) Survey in the Czech Republic: Methodology and History
Bibliographic record
Abstract
EU-SILC is a survey focused mainly on mapping income and living conditions of households. In the Czech Republic, the survey has been conducted annualy since 2005 under the name “Životní podmínky” (Living Conditions). Each year, approximately 10 thousand households are surveyed – around one quarter of these households for the first time, while the rest repeatedly as part of the four-year rotating panel. As the EU-SILC has a uniform methodology for all participating countries, the results for the Czech Republic can be compared with other European countries or with the EU average. The Living Conditions survey was introduced in the context of the Czech Republic´s integration into the EU. However, similar surveys focused on households and their current living situation have been conducted regularly in the former Czechoslovakia since 1956. This article focuses primarily on methodology of SILC, but also offers a brief overview of the living conditions surveys in former Czechoslovakia and in present-day Czech Republic.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".