The probation data included in this dataset is sourced from National Delius (nDelius). nDelius is used for the management of offenders on Probation, or in the community. A service user (offender) is referred to nDelius by a court and an event is created in nDelius. Broadly, events are either a sentence or pre-sentence. An event can only ever have one sentence outcome (disposal). One court case can receive multiple sentences/disposals so more than one event may run at the same time.

A service user will receive one offender_id per court case however duplicates can happen by mistake. The variable estimated_offender_id uses a process of data deduplication to eliminate these duplicates and group them under the same service user cluster.

The accuracy of the source data is dependent on the quality assurance processes and local recording practices intrinsic to the source data systems used by HMPPS staff (nDelius).

The United Nations began its World Crime Surveys in 1978. The first survey collected statistics on a small range of offenses and on the criminal justice process for the years 1970-1975. The second survey collected data on a wide range of offenses, offenders, and criminal justice process data for the years 1975-1980. Several factors make these two collections difficult to use in combination. Some 25 percent of those countries responding to the first survey did not respond to the second and, similarly, some 30 percent of those responding to the second survey did not respond to the first. In addition, many questions asked in the second survey were not asked in the first survey. This data collection represents the efforts of the investigators to combine, revise, and recheck the data of the first two surveys. The data are divided into two parts. Part 1 comprises all data on offenses and on some criminal justice personnel. Crime data are entered for 1970 through 1980. In most cases 1975 is entered twice, since both surveys collected data for this year. Part 2 includes data on offenders, prosecutions, convictions, and prisons. Data are entered for 1970 through 1980, for every even year.

Individuals appearing as defendants in criminal cases dealt with by the magistrates' court in England and Wales (including Youth Courts). Companies appearing as defendants have been excluded.

Prarabdha/indian-legal-data-first dataset hosted on Hugging Face and contributed by the HF Datasets community

This study focused on two of Connecticut's welfare offices, Manchester and New Haven, and used an unusually rigorous research design to provide reliable evidence about Jobs First's impacts -- that is, the difference that Jobs First has made relative to the outcomes generated by the welfare system that preceded it. To facilitate this assessment, between January 1996 and February 1997, several thousand welfare applicants and recipients were assigned, at random, to one of two groups: the Jobs First group, whose members were subject to the welfare reform policies, and the Aid to Families with Dependent Children (AFDC) group, whose members remained subject to the prior welfare rules. People were assigned to the groups through a random process, there were no systematic differences between the groups' members when people entered the study. The two groups experienced the same general economic and social conditions during the study period. Thus, any differences that emerged between the two groups over time -- for example, in employment rates or family income -- can reliably be attributed to Jobs First. The evaluation followed the two groups for four years. The study also collected detailed information about Jobs First's impacts on participants' children, and it includes an analysis comparing the financial benefits and costs of Jobs First for participants and for the government budget.

During a 2020 survey carried out among senior industry experts from companies involved in the use of data and data collaboration from the United States, **** percent of respondents stated they were currently collaborating with a third party to share first-party data for insights, activation, measurements, or attribution; *** percent said they were not collaborating with anybody to such an end but that they used to in the past.

Connecticut's Juvenile Justice Policy and Oversight Committee (JJPOC) has developed this dataset and this dashboard to monitor and examine juvenile justice system involvement across the state for youth of different races, ethnicities, and genders. The following metrics were chosen to understand key points in the juvenile justice system: Delinquent referrals Non-judicial handling Disposition of a first time felony Detention Note: this dataset and the dashboard are being developed in phases, and as of 1/27/2023 they include data on Metric 1: Delinquent referrals and Metric 2: First Time Felony Dispositions. Additional metrics will be added over the course of 2023 and 2024.

The LIDAR Composite First Return DSM (Digital Surface Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The first return DSM is produced from the first or only laser pulse returned to the sensor and includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface where the first or only return was the ground.

Produced by the Environment Agency in 2022, the first return DSM is derived from data captured as part of our national LIDAR programme between 11 November 2016 and 5th May 2022. This programme divided England into ~300 blocks for survey over continuous winters from 2016 onwards. These surveys are merged together to create the first return LIDAR composite using a feathering technique along the overlaps to remove any small differences in elevation between surveys. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The first return DSM will not match in coverage or extent of the LIDAR composite last return digital surface model (LZ_DSM) as the last return DSM composite is produced from both the national LIDAR programme and Timeseries surveys.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

During a 2020 survey carried out among senior industry experts from companies involved in the use of data and data collaboration from the United Kingdom, **** percent of respondents stated they were currently collaborating with a third party to share first-party data for insights, activation, measurements, or attribution; **** percent said they were not collaborating with anybody to such an end but that they used to in the past.

The Global Alien Species First Record Database represents a compilation of first records of alien species across taxonomic groups and regions.

A first record denotes the year of first observation of an alien species in a region. Note that this often differs from the date of first introduction. The database covers all regions (mostly countries and some islands) globally with particularly intense sampling in Europe, North America and Australasia. First records were gathered from various data sources including online databases, scientific publications, reports and personal collections by a team of >45 researchers. A full list of data sources, an analysis of global and continental trends and more details about the data can be found in our open access publication: Seebens et al. (2017) No saturation in the accumulation of alien species worldwide. Nature Communications 8, 14435.

Note that species names and first records may deviate from the original information, which was necessary to harmonise data files. Original information is provided in the most recent files.

Note that first records are sampled unevenly in space and time and across taxonomic groups, and thus first records are affected by sampling biases. From our experience, analyses on a continental or global scale are rather robust, while analyses on national levels should be interpreted carefully. For national analyses, we strongly recommend to consult the original data sources to check sampling methods, quality etc individually.

The first record database will be irregularly updated and the most recent version is indicated by the version number. _Newer Versions_ are accessible via Zenodo_: https://doi.org/10.5281/zenodo.10039630

Here, we provide several files: (1) The annual number of first records per taxonomic group and continent in an excel file, which represents the aggregated data used for most of the analyses in our paper (Seebens et al. Nat Comm). (2) The R code for the implementation of the invasion model used in the paper. (3) A more detailed data set with the first records of individual species in a region. This data set represents only a subset (~77%) of the full database as some data were not publicly accessible. This data set will be irregularly updated and may differ from the data set used in our paper. All data are free of use for non-commercial purposes with proper citation of Seebens et al. (2017) Nat Comm 8, 14435. (4) A substantially updated version of the First Record Database (vs 1.2) used in our second publication: Seebens et al. (2018) Global rise in emerging alien species results from increased accessibility of new source pools. PNAS 115(10), E2264-E2273.

Please, do not ask the contact person for data, but download it at Zenodo: https://doi.org/10.5281/zenodo.10039630 - Thanks!

Irbid First Endowment Directorate data

Link Function: information

During a survey carried out among decision-makers in charge of customer engagement/retention strategy from 20 countries worldwide, ** percent of respondents stated that they thought it was important or critical to collect customer channel engagement data; ************* named real-time experience in this context.

Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).

This dataset contains data collected within limestone cedar glades at Stones River National Battlefield (STRI) near Murfreesboro, Tennessee. This dataset represents interpolated estimates of precipitation (in decimal inches) for 120 quadrat locations (points) within 12 selected cedar glades, for a period of time from 6 days (144 hours) prior to the field visit day up until 3 days (72 hours) prior to the field visit day. At each field visit, precipitation data was collected at four rain gauges installed at STRI. Rain gauge measurements were obtained on the following dates (which correspond to 3 days prior to the fields in the dataset): February 3, 2012; March 2, 2012; March 30, 2012; April 20, 2012; May 22, 2012; June 18, 2012; July 16, 2012; August 20, 2012; September 24, 2012; November 22, 2012, December 14, 2012; January 18, 2013; February 15, 2013; March 16, 2013; April 12, 2013; and May 10, 2013. Points were classified into four groups (identified by the field "Group") and were visited on a rotating sampling schedule, such that each group of points was visited roughly once every four months. ArcGIS version10 software (Esri, Redlands, CA, USA) was used to interpolate a raster surface between these rain gauges so that estimated precipitation values could be assigned to the 120 points used for hydrologic monitoring. First, a raster file was created based on an Inverse Distance Weighted (IDW) algorithm using rain gauge data as inputs, the default output cell size, and the default power of 2. Then, cell values from the interpolated raster were extracted to the 120 hydrologic monitoring points. Missing values (points not measured on a given day) are indicated by the value -99999.Detailed descriptions of experimental design, field data collection procedures, laboratory procedures, and data analysis are presented in Cartwright (2014).References:Cartwright, J. (2014). Soil ecology of a rock outcrop ecosystem: abiotic stresses, soil respiration, and microbial community profiles in limestone cedar glades. Ph.D. dissertation, Tennessee State University.Cofer, M., Walck, J., and Hidayati, S. (2008). Species richness and exotic species invasion in Middle Tennessee cedar glades in relation to abiotic and biotic factors. The Journal of the Torrey Botanical Society, 135(4), 540–553.

https://arxiv.org/pdf/2305.18793 It will also appear at Chapman & Hall.

This dataset contains the data for Individuals serving custodial sentences in England & Wales who appear within records from the prison data source, p-NOMIS.

We propose two analytical relationships between affinity and opinion change. The first one focuses on value homophily, while the second one incorporates affinity in opinion dynamics. Three analytical test models are derived based on these relationships: the value homophily model, the temporal evolution of opinion summation, and the evolution of opinion difference between two individuals. We test these models using data from a previous experiment, and the results demonstrate their validity.