Input datasets on Massachusetts Birth defects data will not be made accessible to the public since they include individual-level data with PII. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The tabulated output data is found in the manuscript. Input data can be obtained from Application process from the owners of the data (Massachusetts Department of Public Health). More details can be found here: https://www.mass.gov/guides/available-public-health-research-data-sets#vital-records. Format: Input datasets on Massachusetts Birth defects data will not be made accessible to the public since they include individual-level data with PII. Output data are all available in tabulated form within the published manuscript (e.g., results of regression models, measures of central tendency, population characteristics, etc.). This dataset is associated with the following publication: Kaufman, J., M. Wright, A. Evans, Z. Rivera-Núñez, A. Meyer, and M. Narotsky. Associations between Disinfection By-Product Exposures and Musculoskeletal Birth Defects. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 4(1): eo81, (2020).

This dataset contains the total first-year retention rates and counts (Fall to Fall) for new first-time, full-time, degree-seeking undergraduate students, disaggregated by gender. It covers all public community colleges and state universities in Massachusetts, and the University of Massachusetts since 2013.

This dataset is 1 of 3 datasets that is also published in the interactive Retention of First-Time, Full-Time Students dashboard on the Department of Higher Education Data Center:

Public Postsecondary First Year Retention: Summary Public Postsecondary First Year Retention by Race Public Postsecondary First Year Retention by Gender

Definitions: - Retention is characterized when a new first-time, full-time student who was enrolled in their first Fall semester is again enrolled in their second Fall semester. - Adjusted Cohort Count: the number of first-year students in a cohort, excluding those who graduated within the first year. - Retained Any Institution is determined by finding students enrolled in the next Fall at other MA Public Institutions using Massachusetts Department of Higher Education data or elsewhere using NSC data. - Cohort identification: These are the Fall Term Credit Students, identified with a cohort when their current registration = New; their New Student Type = Degree-seeking; and enrollment is full-time with >= 12 credits.

Notes: - To comply with data privacy laws, Bucketing is used as a form of data suppression. If a gender category has <= 6 students, then its data is combined with the next largest gender category and the gender is labeled as "Other." - Data appear as reported to the Massachusetts Department of Higher Education.

This dataset contains the total first-year retention rates and counts (Fall to Fall) for new first-time, full-time, degree-seeking undergraduate students, disaggregated by race. It covers all public community colleges and state universities in Massachusetts, and the University of Massachusetts since 2013.

This dataset is 1 of 3 datasets that is also published in the interactive Retention of First-Time, Full-Time Students dashboard on the Department of Higher Education Data Center:

Public Postsecondary First Year Retention: Summary Public Postsecondary First Year Retention by Race Public Postsecondary First Year Retention by Gender

Definitions: - Retention is characterized when a new first-time, full-time student who was enrolled in their first Fall semester is again enrolled in their second Fall semester. - Adjusted Cohort Count: the number of first-year students in a cohort, excluding those who graduated within the first year. - Retained Any Institution is determined by finding students enrolled in the next Fall at other MA Public Institutions using Massachusetts Department of Higher Education data or elsewhere using NSC data. - Cohort identification: These are the Fall Term Credit Students, identified with a cohort when their current registration = New; their New Student Type = Degree-seeking; and enrollment is full-time with >= 12 credits.

Notes: - To comply with data privacy laws, student groups with cohort sizes <= 6 are suppressed. - Data appear as reported to the Massachusetts Department of Higher Education.

This layer contains block level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for the state of Massachusetts. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block level, since this data has been protected using differential privacy.**To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual blocks will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the block itself.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

Effects of data protection on the archive system in the Federal Republic.

Topics: The survey questionnaire is organized in 7 sections:

1. Effects of data protection on the archive: hinderance of one´s own work by legal regulations of data protection; feared impairment of archives in case of extension of data protection legal regulations also to ´files´; perceived tendency to ´over-regulation´; current effects of data protection on archive; resulting refusal of third parties to use archive data due to data protection laws.

2. Legal regulation of acceptance of records from authorities or material registered in the archive: type of legal or administration regulations due to which written material is archived; type of written material that can not be accepted; preservation of written material in trust for authorities; tasks and responsibilities of the archive; perceived restrictive distribution practice of authorities; time limit to acceptance; attitude to storage of personal data on a random basis to reduce a possible data misuse.

3. Mass records: attitude to archiving mass records (scale); refusal by authorities and offices to provide mass records for reasons of data protection; acceptance of mass records within the last 10 years; judgement on one´s own possibilities of continuous acceptance of mass records; presence of systematic plans for preservation or annulment of mass record holdings; interest in recommendations of social scientists for the use of statistical procedures to obtain representative samples from registries of different structure; presence of statistical censuses or surveys since 1945 in personal holdings.

4. Machine-readable data: access to data processing equipment; number of employees with experience in electronic data processing; knowledge about type and amount of machine-readable data accumulating in government offices at the time; judgement on personnel and actual equipment of archive in view of archiving machine-readable data; acceptance of data, complete or on a random basis; characterization of holdings; interest in further archiving; reasons for not yet accepting or reasons for intent to accept machine-readable data in the next few years; effects of use of machine-readable data on archiving process; attitude to preparation and integration of data sets as archive task; assumed future user group with interest in machine-readable data holdings.

5. Tasks and way of working of archive: assessment of archive as information and documentation facility; judgement on selected measures to increase reputation of archive in public (scale); type of acceptance practice of written material by archive; influence of archive on addition of background information to archive holdings; possibilities to estimate future development of holdings; archiving for a limited time documents whose historical value could not be estimated at the time of acceptance; instruments used to record files or develop files; presence of usage statistics; determined changes in composition of users; possibility to classify holdings according to different user groups; perceived change in task of archives in the last few years; expectations of the technical information center for the humanities; securing written material as primary task.

6. Usage regulation: type of usage regulation; presence of usage time limits and conditions for use; type of written material with use time limits; time of sole decision about the usability; modalities of use of holdings; usage regulations and data protection; access modalities for research; perceived change of archive task.

7. Archive laws: probability of a new archive law coming to be; judgement on legal basis of archive up to now and for future requirements of data protection; attitude to the function of archive laws, both to satisfy the need to protect the citizen as well as to meet the information needs of historical research; most important archive tasks needing to be regulated by an archive law; judgement on a usage restriction for authorities after archiving; judgement on practicality of a general right to access and information for persons affected; assumed number of such queries; desire for stronger effort on the part of scientific users for the interests of the archive system; presence of sources containing information on marriages in the time period from 1800 to 1945; superior department; number and course of training of employees.

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Private Security Services Market Size 2025-2029

The private security services market size is forecast to increase by USD 259.4 billion, at a CAGR of 11.9% between 2024 and 2029.

The market is experiencing significant growth and transformation, driven by the rapid urbanization and population growth that necessitate increased security measures. This trend is particularly pronounced in developing regions, where the demand for private security services is surging to address the rising crime rates and ensure public safety. Another key driver is the increasing popularity of virtual security systems, which offer cost-effective and efficient solutions for monitoring and securing properties. However, the market faces a significant challenge in the form of a shortage of private security personnel. This labor shortage is exacerbated by the growing complexity of security threats and the need for highly skilled personnel to effectively mitigate risks. Companies seeking to capitalize on market opportunities must invest in technology and training to address the labor shortage and stay competitive. Additionally, they must adapt to the changing security landscape by offering integrated security solutions that combine physical and virtual security measures. By doing so, they can effectively address the evolving needs of clients and navigate the challenges of the market.

What will be the Size of the Private Security Services Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, with dynamic market dynamics shaping the industry's applications across various sectors. Threat analysis and penetration testing are crucial components of data protection, ensuring security standards are met and maintained. Security awareness campaigns, event correlation, and policy adherence are integral to ransomware protection and cybersecurity. Security technology, including analytics platforms and automation, plays a significant role in security education and assessment. Physical security, consulting, and intelligence are essential for perimeter security and incident management. Regulations such as PCI DSS and privacy laws necessitate compliance audits and security integration. Vulnerability assessments and management are ongoing processes that involve security infrastructure, asset protection, and best practices. Security breaches and phishing prevention require robust emergency response and incident management capabilities. Disaster recovery planning and background checks are essential components of business continuity planning and security management systems. Security architecture and operations centers ensure security monitoring and reporting, while security certifications and outsourcing provide additional layers of protection. Network security, malware protection, and CCTV surveillance are integral to security hardware and software solutions. Threat intelligence and risk management are essential for maintaining a strong security culture and effective security testing.

How is this Private Security Services Industry segmented?

The private security services industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userIndustrialResidentialFinancial institutionsOthersServiceManned guardingElectronic security servicesCash servicesGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW).

By End-user Insights

The industrial segment is estimated to witness significant growth during the forecast period.The market encompasses various offerings such as loss prevention, penetration testing, data protection, security standards, security awareness campaigns, security event correlation, security policies, ransomware protection, security technology, security analytics platform, security analytics, security training, cybersecurity training, security automation, security orchestration, security education, security assessments, physical security, security consulting, security intelligence, security protocols, business continuity planning, security planning, data privacy, perimeter security, security audits, security integration, security management systems, security architecture, security operations center, security monitoring, PCI DSS, security outsourcing, security hardware, security awareness, threat analysis, access control systems, red teaming, vulnerability management, security infrastructure, asset protection, best practices, security breaches, phishing prevention, emergency response, data breaches, privacy laws, vulnerability assessments, security regulations, security incident ma