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Data Management and Sharing Plan for: Adaptation and Preliminary Evaluation of Energize-MBC: Cognitive Behavioral Therapy for Fatigue among Women with Metastatic Breast Cancer
No full textThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data
Data Management and Sharing Plan for: The effect of endogenous and exogenous glucocorticoids acting through regulatory T cells on resolution of ALI and the contribution of host genetic variability.
No full textThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data
Data Management and Sharing Plan for: MSA Centers of Excellence
No full textThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data
All Student Measures, Child, Early Education in Rural North Carolina
No full textThe Early Education in Rural North Carolina project was one of the 6 research sites in the Early Learning Network, investigating the impact of policy context surrounding a cohort of children as they progressed from prekindergarten through third grade in six rural counties. The North Carolina (NC) team focused on whether policies were aligned in ways to sustain learning across the early grades. This project collected semi-structured interviews, survey data from school and program administrators, observations, and content analysis of policy documents.
This record includes a dataset that combines all the measures collected on participating students, including Dynamic Indicators of Basic Early Literacy Skills (DIBELS), Expressive One-Word Picture Vocabulary Test (EOWPVT-4), NIH Toolbox Cognition Battery (NIHTB-CB), and Woodcock-Johnson III (WJ III), among others
Monmouth University Pennsylvania Poll, Number 258
No full textThis survey was conducted among Pennsylvania voters and address the 2022 election for U.S. Senate and issues facing the state
Data Management and Sharing Plan for: High throughput functional studies of IBD-associated GWAS variants
No full textThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data
Location of Index Minerals within Watauga and Ashe County north of Boone, NC
No full textThis dataset contains the locations in which index minerals were identified within thin section or outcrop. These locations are within the Ashe and Alligator Back Metamorphic Suites north of Boone, NC
Romantic Self-Presentation in Date-Me Docs, 2024
No full textThis study employed natural language processing (NLP) techniques to explore shared themes and variations in romantic self-presentation strategies in “Date-Me Docs”— recently popularized web-based longform personal advertisements for online dating.
251 usable profiles were sourced from a publicly available directory of Date-Me-Docs (https://dateme.directory/) after omitting 108 documents which were inaccessible or blank (e.g., due to a change in site permissions), one document which contained less than 50 characters, and four documents which were not written in English. The average word count for the dataset is 972 (SD = 1006), with an average of 27 (SD = 18) words per sentence. The authors are 59.6% male (36.4% female, 4% non-binary; 0.40% undisclosed), 73.9% monogamous (18.3% open to both monogamy and polyamory, 7.8% polyamorous; 8.4% undisclosed), 84% straight (i.e., “M” interested in “F” or “F” interested in “M”) and have a mean age of 32.5 (SD = 7.3) years. In terms of childcare intention, 46.3% of authors indicated they “want kids” (32.9% “might want kids”, 17.6% “do not want kids”, 3.2% “has kids”; 13.9% undisclosed). Authors also provided their location, location flexibility (i.e., how willing they are to move), and community affiliation (Effective Altruism (EA), Tech, and/or Rationalism).
After pre-processing the unstructured text data, the corpus was converted into a document-feature matrix where the rows represent documents, columns represent terms (768 in this dataset after cleaning), and values represent the frequency of the term’s appearance in a specific document. This matrix contained the features (i.e., document terms) that were used as variables in topic modeling with Latent Dirichlet Allocation (LDA) to identify shared themes and topic distributions over documents.
Topic modeling revealed ten distinct themes spanning personal preferences, self expansion and growth, open communication, and social responsibility. The topics (and their definitions; % of total) were: Altruism (Desire to contribute to societal well-being; 14.3%), Expectations (Specific expectations for a long-term relationship; 11.2%), Collectivism (Strong connection with others & the world; 10.6%), Dialogue (Intellectual curiosity & exchange; 10.6%), Lifestyle (Conventional life choices, especially children, monogamy, and substance use; 9.5%), Learning (Learning & experiencing aspects of the world; 9.1%), Socializing (Casual socializing, including entertainment; 9.1%), Hobbies (Creative & fulfilling leisure activities; 9%), Goals (Building towards a better future; 8.4%), and Activity (Physical activity, exercise, and traveling; 8.3%).
Other descriptive information about the documents were also gathered (e.g., punctuation, numbers, symbols, URLs, tags, emojis), and each document was rated on various positive and negative emotions (e.g., anger, anticipation, disgust, fear, joy, sadness, surprise, trust).
This study was exempt from ethics board approval, as the data were publicly accessible
Data Management and Sharing Plan for: Regulatory Genomics of Ozone Air Pollution Response in Vitro and In Vivo
No full textThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data
Zanzibar Clinic Data
No full textDe-identified clinic data for the paper "Integrating mobility, travel survey, and malaria case data to understand drivers of malaria importation to Zanzibar, 2022–2023." This dataset includes variables on case demographics and reported travel history