The ParlaMint corpora of parliamentary proceedings.

This paper presents the ParlaMint corpora containing transcriptions of the sessions of the 17 European national parliaments with half a billion words. The corpora are uniformly encoded, contain rich meta-data about 11 thousand speakers, and are linguistically annotated following the Universal Dependencies formalism and with named entities. Samples of the corpora and conversion scripts are available from the project's GitHub repository, and the complete corpora are openly available via the CLARIN.SI repository for download, as well as through the NoSketch Engine and KonText concordancers and the Parlameter interface for on-line exploration and analysis.

Risky health behaviours and socioeconomic inequalities in European countries: new insights from European Social Survey.

OBJECTIVES: This paper explores education-, income- and occupational class-related inequalities in risky health behaviours including into models all three factors together as well as their interactions, which has not been undertaken by previous studies analysing socioeconomic status (SES) related differences in risky health behaviours. METHODS: Our data source is the special module "Social Inequalities in Health" included into the European Social Survey Round 7 (ESS R7) and conducted in 20 European countries. We run nine separate multilevel binomial logistic regression analyses for all the risky health behaviours with all our independent and control variables including country as the second level random intercept. Into all the models we also included interaction terms to consider possible moderating effects of separate independent variables. RESULTS: Education and income emerged as factors most consistently related to risky health behaviours, but occupational class differences were also found to be significant: eating vegetables or salad less than once a day and being daily smoker is positively related to lower SES as measured by all three indicators; eating fruits less than once a day is related to lower income and occupational class, while drinking alcohol at least several times a week is positively related to higher education and higher income; being physically active for less than 3 days per week is positively related to lower education; patterns of heavy smoking and binge drinking are inconsistently related to SES variables. We also found considerable regional variation, especially in fruit and vegetable consumption, being physically active and alcohol consumption patterns. CONCLUSIONS: Without careful theoretical consideration linking SES and risky health behaviours, education, income and occupational class cannot substitute each other in the study of SES-related differences of health behaviours, as assumed in the larger part of research on the subject.