Institutional Trust in the World 1995-2022: Data files and info - world
Bibliographic record
Abstract
This dataset includes data files on the individual data of all respondents to international surveys conducted and published between 1995 and 2022, including data on trust in institutions. It also includes answers to three questions about democracy, covering satisfaction, appreciation of the level of democracy, and support for democracy. There are several files: 1) a general file including all combined and harmonized data. 2) a file including the same data but only for respondents who answered at least one question on trust. The next four files allow for a four-level multilevel analysis with HLM, with one file per level: 3) a file at the measurement level (level 1), including one line per trust-related response, per respondent 4) a file including only information on respondents (level 2); 5) a file including information on surveys - and thus on country-year-data source (level 3); 6) a file including information on countries combined with data sources -- region - characteristics of sources. All files include identifiers for the country, year, and data source. Cet ensemble de données comprend les fichiers de données relatifs aux données individuelles de tous les répondants aux sondages internationaux réalisés et publiés entre 1995 et 2022 comprenant des données sur la confiance dans les institutions. Il comprend également les réponses à trois questions sur la démocratie portant sur la satisfaction, l'appréciation du niveau de démocratie et l'appui à la démocratie. Il y a plusieurs fichiers: 1) un fichier général comprenant toutes les données combinées et harmonisées. 2) un fichier comprenant ces mêmes données mais uniquement pour les répondants qui ont répondu à au moins une questions sur la confiance. Les quatre fichiers suivants permettent de faire une analyse multiniveaux à quatre niveaux avec HLM, soit un fichier par niveau 3) un fichier au niveau des mesures (niveau 1), comprenant une ligne par réponse relative à la confiance, par répondant 4) un fichier comprenant uniquement les informations sur les répondants (niveau 2); 5) un fichier comprenant les informations sur les sondages - et donc sur les pays-années-sources de données (niveau 3) 6) un fichier comprenant les informations sur les pays combinés aux sources de données -- région - caractéristiques des sources. Tous les fichiers comprennent des identifiants pour le pays, l'année et la source des données.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.021 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.057 | 0.029 |
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".