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41 results for “Legislative”
Data from: What is a disease? Perspectives of the public, health professionals, and legislators
Objective: To assess the perception of diseases and the willingness to use public tax revenue for their treatment among relevant stakeholders. Design: A population-based, cross-sectional mailed survey. Setting: Finland Participants: 3 000 laypeople, 1 500 doctors, 1 500 nurses (randomly identified from the databases of the Finnish Population Register, the Finnish Medical Association and the Finnish Nurses Association), and all 200 parliament members. Main outcome measures: Respondents' perspectives on a 5-point Likert scale on two claims on 60 states of being: "[This state of being] is a disease"; and "[This state of being] should be treated with public tax revenue". Results: Of the 6 200 individuals approached, 3 280 (53%) responded. Of the 60 states of being, ≥80% of respondents considered 12 to be diseases (Likert scale responses of "4" and "5") and five not to be diseases (Likert scale responses of "1" and "2"). There was considerable variability in most states, and great variability in ten (≥20% of respondents of all groups considered it a disease and ≥20% rejected as a disease). Doctors were more inclined to consider states of being as diseases than laypeople; nurses and parliament members were intermediate (p<0.001), but all groups showed large variability. Responses to the two claims were very strongly correlated (r = 0.96 [95% CI: 0.94-0.98]; p<0.001). Conclusions: There is large disagreement among the public, health professionals, and legislators regarding the classification of states of being as diseases and whether their management should be publicly funded. Understanding attitudinal differences can help to enlighten social discourse on a number of contentious public policy issues.
EU legislation published between 1971-2022
<p><strong>EU Legislation Documents and Metadata from 1971 to 2022 (English language)</strong></p> <p>This is the set of full text regulation, decision and directive documents in <a href="https://en.wikipedia.org/wiki/PDF">PDF</a> and <a href="https://en.wikipedia.org/wiki/HTML">HTML</a> format, in the English language, downloaded from <a href="https://eur-lex.europa.eu/">EURLEX</a>, together with metadata in <a href="https://en.wikipedia.org/wiki/Comma-separated_values">CSV format</a> about these documents. The documents were downloaded using <a href="https://github.com/nature-of-eu-rules/data-extraction/blob/main/eu_rules_fulltext_extractor.py">this Python script</a>, and the metadata was extracted from the <a href="https://op.europa.eu/en/publication-detail/-/publication/658088eb-c071-11e8-9893-01aa75ed71a1/language-en/format-PDF/source-76875949">CELLAR</a> <a href="http://publications.europa.eu/webapi/rdf/sparql">SPARQL endpoint</a> using <a href="https://github.com/nature-of-eu-rules/data-extraction/blob/main/eu_rules_metadata_extractor.py">this Python script</a>.</p> <p>During the download process, HTML versions for the legislative documents were extracted if they were available. If there was no HTML version available for a particular document, the PDF version was downloaded (HTML versions were preferred because it is generally simpler to extract and process the text with software because of the added structure the format provides). If there was neither an HTML nor PDF version available, we made a note of the unique identifier (<a href="https://eur-lex.europa.eu/content/help/eurlex-content/celex-number.html">CELEX</a> number) for those documents. The archive in this <a href="https://zenodo.org/">Zenodo</a> repository which contains all the full text documents consists of three directories "htmls/", "pdfs/" and "problems/", which contain all the downloaded documents in that particular format. The "problems/" directory contains a list of blank <a href="https://en.wikipedia.org/wiki/Text_file">.txt</a> files where the name of each file is the CELEX number for a legislative document that was not available on EURLEX for download.</p> <p>For more information about the scripts and a description of the metadata extracted, please see <a href="https://github.com/nature-of-eu-rules/data-extraction">this Github repository.</a></p> <p>The data was extracted as part of the <a href="https://research-software-directory.org/projects/the-nature-of-eu-rules-strict-and-detailed-or-lacking-bite">Nature of EU Rules</a> project which seeks to analyse the "strictness" and density of EU regulations over time and by legal policy area.</p> <p> </p>
Impact of Smoke-free Legislation on Early-life Mortality and Low Birth Weight in England
ClinicalTrials.gov study NCT02039583. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Assessing the Impact of Smoke-free Legislation on Perinatal Health in the Netherlands
ClinicalTrials.gov study NCT02189265. IPD Sharing: Not stated. Countries: 2. Publications: 8.
Data from: A prioritised list of invasive alien species to assist the effective implementation of EU legislation
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Data from: What is a disease? Perspectives of the public, health professionals, and legislators
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Canada's common law species at risk legislation scoring rubric and provincial conservation plans for listed species at risk
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Data from: Is environmental legislation conserving tropical stream faunas? a large-scale assessment of local, riparian and catchment-scale influences on Amazonian stream fish
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Data from: Abortion legislation, maternal healthcare, fertility, female literacy, sanitation, violence against women, and maternal deaths: a natural experiment in 32 Mexican states
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Database of Past and Present Alien Invasive Species-Related Policy and Legislation in South Africa
<p>A full list of all laws relevant to biological invasions in South Africa since 1861</p>
Schönberg, J., Böhm-Beck, M., Trdan, Š., Grego, M., Knoblauch, D., Hinzmann, M., Dittmann, S., Knickmeier, K., Robič, U., Thiel, M., Kiessling, T., 2025. Public participation in EU legislation? Recommendations for involving citizen scientists in anthropogenic litter research within the Water Framework Directive.
<p>Research data and figures to the manuscript "Public participation in EU legislation? Recommendations for involving citizen scientists in anthropogenic litter research within the Water Framework Directive" by Schönberg et al. 2025</p>
ANALYSIS OF INTERNATIONAL AND NATIONAL HUMAN RIGHTS LEGISLATION
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FOREIGN EXPERIENCE AND BASICS OF NATIONAL LEGISLATION ON IMPROVING THE LIFE OF THE POPULATION
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Supplementary material 1 from: Foster R, Peeler E, Bojko J, Clark PF, Morritt D, Roy HE, Stebbing P, Tidbury HJ, Wood LE, Bass D (2021) Pathogens co-transported with invasive non-native aquatic species: implications for risk analysis and legislation. NeoBiota 69: 79-102. https://doi.org/10.3897/neobiota.69.71358
Table S1
Supplementary material 2 from: Foster R, Peeler E, Bojko J, Clark PF, Morritt D, Roy HE, Stebbing P, Tidbury HJ, Wood LE, Bass D (2021) Pathogens co-transported with invasive non-native aquatic species: implications for risk analysis and legislation. NeoBiota 69: 79-102. https://doi.org/10.3897/neobiota.69.71358
Table S2
Supplementary material 3 from: Foster R, Peeler E, Bojko J, Clark PF, Morritt D, Roy HE, Stebbing P, Tidbury HJ, Wood LE, Bass D (2021) Pathogens co-transported with invasive non-native aquatic species: implications for risk analysis and legislation. NeoBiota 69: 79-102. https://doi.org/10.3897/neobiota.69.71358
Table S3
Reproducibility data for a study of regulatory statements in EU legislation
<p><strong>Reproducibility data for a quantitative study on EU legislation</strong></p> <p>The files in this repository were generated or used in a pipeline of analysis operations on EU legislation published between 1971 and 2022. The project is called the <a href="https://research-software-directory.org/projects/the-nature-of-eu-rules-strict-and-detailed-or-lacking-bite">Nature of EU Rules</a> which seeks to analyse the "strictness" and density of EU regulations over time and by legal policy area. The data has been made available to help make the results of our study reproducible by other researchers. The underlying data used in the study has also been published in <a href="https://doi.org/10.5281/zenodo.8174175">this repository</a>.</p> <p><strong>File descriptions</strong></p> <ol> <li>complete_training_data.csv <ul> <li>This file is training data for binary classification of specific sentences in EU legislation as either regulatory in nature (constituting a legal obligation for some agent) or not (called a constitutive statement). The sentences have been labelled by EU law professors from Aarhus University in Denmark and Radboud University in the Netherlands</li> <li><strong>Note:</strong> The file also contains columns for identifying the specific agent being regulated (to which the legal obligation applies) in each sentence. However, this information has not been used in the study</li> </ul> </li> <li>extracted_sentences_classified_1971_2022.csv <ul> <li>List of sentences extracted from EU legislation documents</li> <li>Classification results for individual sentences whether each is regulatory or not. There are two columns recording the classification results, one for a rule-based approach (using <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/rule-based-classification.py">grammatical dependency parsing</a>) and one for a <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/inlegalbert-classification.py">LegalBERT classification</a> approach.</li> </ul> </li> <li>inlegal_bert_xgboost_classifier.json <ul> <li>Trained binary classification model for classifying sentences as regulatory or not (based on <a href="https://huggingface.co/law-ai/InLegalBERT">InlegalBERT</a>).</li> <li>Note: this model is trained on the file 'complete_training_data.csv' in this Zenodo repo</li> <li>Model was trained using <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/train_inlegalbert_xgboost.py">this script</a> and used by these scripts: <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/classify_text_with_inlegal_bert_xgboost.py">one</a>, <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/inlegalbert-classification.py">two</a></li> </ul> </li> <li>metadata_enriched.csv <ul> <li>Metadata file from <a href="../record/8174176">this repository</a> but enriched with additional columns one of which is the count of regulatory sentences in each individual document</li> <li>File is generated by <a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis/blob/main/prepare-data-for-analysis.py">this script</a></li> <li>File is used by <a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis/blob/main/analysis.py">this script</a></li> </ul> </li> <li>classification_results_all_algorithms_test_set.csv <ul> <li>classification results of each sentence in the test set containing 1451 sentences (20% of training set)</li> <li>according to both the fine-tuned Legal-BERT model and the dependency parsing (rule-based) algorithm</li> <li>also contains the ground truth labels</li> </ul> </li> </ol> <p><strong>Github repositories relevant to this analysis</strong></p> <p>The Python scripts in the following Github repositories were responsible for generating the data files in this Zenodo repository. The first repository listed is the core one for running the pipeline to classify and quantitatively analyse legal obligations in EU legislation. The other listed Github repositories represent components or steps of the pipeline.</p> <ul> <li><a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis"><strong>http://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis</strong></a> <ul> <li><a href="https://github.com/nature-of-eu-rules/data-extraction"><strong>http://github.com/nature-of-eu-rules/data-extraction</strong></a></li> <li><a href="https://github.com/nature-of-eu-rules/data-preprocessing"><strong>http://github.com/nature-of-eu-rules/data-preprocessing</strong></a></li> <li><a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification"><strong>http://github.com/nature-of-eu-rules/regulatory-statement-classification</strong></a></li> </ul> </li> </ul> <p> </p>
Italian Legislative Property Graph
<p>Property Graph for the Italian legislative system that we presented in the paper <strong>Modelling Legislative Systems into Property Graphs to Enable Advanced Pattern Detection</strong> submitted to CIKM 2024 - Applied Research</p>
Cigar Legislation and Regulation in Tobacco for the Young (Project CLARITY)
ClinicalTrials.gov study NCT07162935. IPD Sharing: YES. Countries: 1. Publications: 0.
Parental Views Related to Colorado State Legislation About Vaccinations, Schools, and Child Care Centers
ClinicalTrials.gov study NCT02957344. IPD Sharing: NO. Countries: 1. Publications: 0.
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