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This repository contains the processed country-period (panel) dataset and the Stata code used to reproduce the empirical results reported in the article “Government Size, Civic Capital and Economic Performance: An O-ring Approach.” The original respondent-level EVS and WVS datasets are not redistributed and must be obtained directly from the respective data providers. The repository contains only the authors’ derived country-period aggregates.

This dataset provides the musical score transcription for Exercise No. 39 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

This dataset provides the musical score transcription for Exercise No. 38 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

This dataset provides the musical score transcription for Exercise No. 44 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

The ANPRIND Character-Detection dataset is a curated collection designed for character-level labeling in Indian vehicle number plate detection. This dataset provides a valuable resource for training and evaluating computer vision models focused on Automatic Number Plate Recognition (ANPR) at the character detection stage. It contains a total of 8,168 images, with characters annotated in COCO format using Roboflow’s annotation tools to ensure accuracy and consistency. To prepare the dataset, each image underwent standardized pre-processing, including auto-orientation of pixel data with EXIF stripping, resizing to a uniform 640x640 resolution, and conversion to grayscale (CRT phosphor) to enhance clarity for character recognition tasks. To further improve dataset diversity and robustness, three augmented versions of each source image were generated. The augmentation techniques included horizontal and vertical flips with a 50% probability, equal probability of 90-degree rotations (none, clockwise, counter-clockwise, upside-down), random rotations between -15° and +15°, and random Gaussian blur ranging from 0 to 2.5 pixels. These augmentations simulate real-world variability and strengthen model generalization. The dataset is particularly suited for developing character-level ANPR systems tailored to Indian number plates, supporting applications such as traffic law enforcement, vehicle tracking, and smart city initiatives. By leveraging Roboflow’s annotation and export capabilities, the dataset ensures reproducibility and compatibility with modern computer vision pipelines. Researchers can also integrate it seamlessly into training workflows and extend its use for academic and applied projects in intelligent transportation systems. In summary, ANPRIND Character-Detection offers a high-quality, well-annotated dataset with diverse augmentations, making it a strong foundation for advancing research and applications in Indian vehicle number plate character detection.

This dataset provides the musical score transcription for Exercise No. 45 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

This dataset provides the musical score transcription for Exercise No. 51 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

This dataset provides the musical score transcription for Exercise No. 54 from the Paschoal Bona method, in both standard notation and Braille. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians.

This dataset provides an accessible musical arrangement of the work "Não foi com Ouro" for alto saxophone, presented in both standard musical notation and Braille music notation. The piece was originally composed by Margaret Jenkins Harris. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians. Reference: https://hymnary.org/text/i_will_praise_him_i_will_praise_him_pr. Accessed on: Sept. 11, 2026.

This dataset provides an accessible musical arrangement of the work "Não foi com Ouro" for alto saxophone, presented in both standard musical notation and Braille music notation. The piece was originally composed by James M. Gray. The material includes files containing the standard score (print notation), print-ready Braille notation files, and editable source files for the MusiBraille music notation software. This resource was developed within the context of research into assistive technology and inclusive music education. The dataset serves as an open educational resource and a technical product designed to support the teaching, learning, and accessible instrumental practice of visually impaired musicians. Reference: https://biblia.teo.br/harpa/hino/231/nao-foi-com-ouro/historia. Accessed on: Sept. 11, 2026.