These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. Teenage adolescent females residing in Baltimore, Maryland who were involved in a relationship with a history of violence were sought after to participate in this research study. Respondents were interviewed and then followed through daily diary entries for several months. The aim of the research was to understand the context regarding teen dating violence (TDV). Prior research on relationship context has not focused on minority populations; therefore, the focus of this project was urban, predominantly African American females. The available data in this collection includes three SAS (.sas7bdat) files and a single SAS formats file that contains variable and value label information for all three data files. The three data files are: final_baseline.sas7bdat (157 cases / 252 variables) final_partnergrid.sas7bdat (156 cases / 76 variables) hart_final_sas7bdata (7004 cases / 23 variables)

This dataset provides the information on relationships between concepts or atoms known to the Metathesaurus for the semantic type "Finding". In the dataset, for asymmetrical relationships there is one row for each direction of the relationship.

Most people seek to establish romantic or intimate relationships in life, including people with mental health problems. However, this has been a neglected topic in mental health practice and research. This study aimed to investigate views of mental health and social care staff about the appropriateness of helping service users with romantic relationships, barriers to doing this, and suggestions for useful ways to support this. An online survey comprising both closed, multiple response and free-text questions was circulated to mental health organisations across the U.K. via social media, professional networks and use of snowballing sampling. A total of 63 responses were received. Quantitative data were analysed using descriptive statistics, and are reported as frequencies and percentages. Qualitative data were interpreted using thematic analysis, using an inductive approach. Although most participants reported that ‘finding a relationship’ conversations were appropriate in their job role, many barriers to supporting service users were identified, including: a lack of training; concerns about professional boundaries; concerns about service user capacity and vulnerability; and concerns about being intrusive. Participant suggestions for future support included educating service users on safe dating behaviours, and practical interventions such as assisting service users to use dating sites and engage with social activities to develop social skills and meet others. Staff were willing to help service users seek an intimate relationship but may need specific training or guidance to facilitate this confidently and safely. This study elucidates the need for further research in this area, particularly in understanding service user perspectives, and in developing resources to support staff in this work.

This data set includes a row for each type of non-appointment relationship between an insurance agent, agency, adjuster, and businesses and an insurance company or another person or business approved to manage insurance-related products or claims. To view a list of formal designations, or appointments, for agents to represent a regulated company, go to Active insurance company appointments for agents and adjusters. To view a list of formal designations, or appointments, for agencies to represent a regulated company, go to Active insurance company appointments for agencies and businesses.

Trust between couples is a prerequisite for stable and satisfactory romantic relationships. However, there has been no valid research tool to assess partner-specific trust behavior including costly investments in the trustworthiness of the romantic partner. We here present a comprehensive validation of the newly developed Trust Game for Couples (TGC) by means of various self-report and implicit relationship-related measures. The TGC operationalizes trust by measuring an individual’s willingness to invest his or her own financial resources in pro-relationship attitudes of their romantic partner (collected by dichotomous responses to relationship-relevant items, e.g., answering yes to “I am absolutely sure that I love my partner”). Thirty-five healthy couples between 20 and 34 years completed the TGC in an interactive (both partners present), but anonymous setting (no information on the partner’s responses revealed). Trust, as measured by the TGC, correlates positively with self-reported trust, satisfaction, and felt closeness in the relationship, but not with general interpersonal trust, confirming both its convergent and discriminant validity. In addition to explicit criteria for construct validity, implicit measures of partner valence and confidence explained variance in the TGC, demonstrating that it constitutes an economical measure of implicit and explicit ingredients of trust between couples. In sum, the TGC provides a novel, specific behavioral tool for a sensitive assessment of trust in dyadic relationships with potential for numerous research fields.

According to a survey carried out in Hong Kong in April 2022, around **** percent of female respondents admitted that they had been in an open relationship. Only slightly smaller proportion of men - ** percent - confirmed having such experience.

ACF Agency Wide resource

Metadata-only record linking to the original dataset. Open original dataset below.

Financial overview and grant giving statistics of Relationship Networking Industryassociation Inc

The Online Relationship Advice Platforms market is experiencing rapid growth as individuals increasingly seek guidance on personal relationships through digital means. These platforms provide a range of services, including one-on-one consultations with relationship experts, moderated forums for peer support, and edu

This data set includes all verified Intimate Partner Violence occurrences investigated by Toronto Police Service by reported date since 2014. The Intimate Partner Violence categories include Family, Intimate Partner, and Unclassified. Count is an aggregated count of Intimate Partner Violence by fields listed in the dataset.Intimate Partner Violence DashboardDownload DocumentationDefinitions:FamilyFamilial relationships such as parents, siblings, or any other family members.Intimate PartnerThe TPS IPV Procedure defines an Intimate Relationship as "marriage, domestic partnership, engagement, casual or serious romantic involvement, and dating, whether in a current or former relationship. Intimate Partner Violence can occur between persons of any sex, sexual orientation, gender, gender identity, or gender expression, and it can occur in any type of intimate relationship including monogamous, non- committed, and relationships involving more than two partners.Intimate Relationship – DatingIntimate Relationship - Dating means marriage, domestic partnership, engagement, casual or serious romantic involvement, and dating, whether in a current or former relationship. Intimate Partner Violence can occur between persons of any sex, sexual orientation, gender, gender identity, or gender expression, and it can occur in any type of intimate relationship including monogamous, non-committed, and relationships involving more than two partners.Intimate Partner ViolenceIntimate Partner Violence means any physical, sexual or psychological harm caused, or attempted, between persons involved in an intimate relationship including: • assault;• murder;• sexual assault;• threatening;• harassment;• intimidation;• unlawful interference with personal liberty;• any other criminal offence;• offences under other statutes, such as the Family Law Act, Children’s Law Reform Act, etc.;but does not include child abuse investigations.UnclassifiedThe relationship between the victim and the accused in the occurrence is not identified or indicated but the investigating officers have identified this as an intimate partner related incident. This data only includes confirmed Intimate Partner Violence crimes. This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The location of Intimate Partner Violence occurrences have been grouped to the fields in the dataset to protect the privacy of the parties involved in the occurrence. By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data.** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

A fundamental question of any new relationship is, will it last? Transient relationships, recently defined by the authors, are an ideal type of social tie to explore this question: these relationships are characterized by distinguishable starting and ending temporal points, linking the question of tie longevity to relationship finite lifetime. In this study, we use mobile phone data sets from the UK and Italy to analyze the weekly allocation of time invested in maintaining transient relationships. We find that more relationships are created during weekdays, with a greater proportion of them receiving more contact during these days of the week in the long term. The smaller group of relationships that receive more phone calls during the weekend tend to remain active for more time. We uncover a sorting process by which some ties are moved from weekdays to weekends and vice versa, mostly in the first half of the relationship. This process also carries more information about the ultimate lifetime of a tie than the part of the week when the relationship started, which suggests an early evaluation period that leads to a decision on how to allocate time to different types of transient ties.

ABSTRACT This study aimed to evaluate the psychometric properties of the Brazilian version of the reduced Love Components Scale. Participants were 491 people in loving relationships. Exploratory factor analysis extracted three factors that explained 73.5% of the common variance that did not reproduce the original structure. The factors showed moderate to strong correlations with each other and with the components of the reduced Triangular Love Scale. The Schmid-Leiman solution indicated the existence of a second-order factor. The reliability coefficients revealed a high internal consistency for all dimensions of the instrument. Additional exploratory factor analysis with the set of items of the two measurements revealed structural indications that they may represent the same components of love.

Economically Active Population Survey: Population by family relationship to the reference person, sex and age group. Quarterly. National.

This data set contains pre and post workshop survey level data of TechnoLOVE workshops conducted by the New York City Healthy Relationship Academy between 2010 and 2018.

Financial overview and grant giving statistics of Relationship Equality Foundation Inc

SA3 based data for Relationship in Household by Age by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of persons in occupied private dwellings categorised by the relationship of each …Show full descriptionSA3 based data for Relationship in Household by Age by Sex, in Place of Enumeration Profile (PEP), 2016 Census. Count of persons in occupied private dwellings categorised by the relationship of each person in a family to the family reference person or, where a person is not part of a family, that person's relationship to the household reference person. Excludes persons in 'Other non-classifiable' households. Includes same sex couples. P23 is broken up into 2 sections (P23a - P23b), this section contains 'Males Husband in a registered marriage Age 15-24 years' - 'Females Other related individual Total'. The data is by SA3 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

Individuals can report more than one race category. This table maps the individual recipient's ID (from the Individual Recipients - HMIS Data Standards dataset) to HMIS Race ID (from the Race - HMIS Data Standards dataset).-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=61082

Comprehensive YouTube channel statistics for Love Marriage Couple vlog, featuring 262,000 subscribers and 191,337,423 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in IN. Track 1,778 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Occupational accident statistics, relationship between types of accidents and injured body parts by manufacturing sector (annual) data

Review of Economics and Statistics: Forthcoming.b