Ireland Census contains records from Scalp, Peterswell, County Galway, Ireland by Class: RG14; Census of Ireland 1901/1911. The National Archives of Ireland. http://www.census.nationalarchives.ie/search/: accessed 31 May 2013; Ancestry.com. Web: Ireland, Census, 1911 [database on-line]. Provo, UT, USA: Ancestry.com Operations, Inc., 2013. - .

This spreadsheet is designed to be used in conjunction with the Integrated Census Microdata (I-CeM) collection of historic census data covering the period 1851 to 1921. For further details of the I-CeM data collection, please visit the comprehensive project website at:

https://www.campop.geog.cam.ac.uk/research/projects/icem/

Outline information on the I-CeM project are also provided on the README page of this spreadsheet.

This file is specifically related to the I-CeM data collection variable HOLLEROCC

The CCRI microdata are based on a five percent sample of the Canadian population as recorded in the 1911 census. The basic sample unit is the dwelling, as defined by the census. The sample includes all responses recorded on the population schedule for all individuals residing in each sampled dwelling. For each census, the main sample covers smaller dwellings with no more than thirty residents. The CCRI microdata facilitate research on individuals, families, households, and communities caught up in the complex transformation of Canadian society which took place during the first half of the twentieth century. Ultimately, these data represent the raw materials with which census statistics can be produced. Confidential data from subsequent census enumerations are available from Statistics Canada's Research Data Centres.

This spreadsheet is designed to be used in conjunction with the Integrated Census Microdata (I-CeM) collection of historic census data covering the period 1851 to 1921. For further details of the I-CeM data collection, please visit the comprehensive project website at:

https://www.campop.geog.cam.ac.uk/research/projects/icem/

Outline information on the I-CeM project are also provided on the README page of this spreadsheet.

This file is specifically related to the I-CeM data collection variable HOLLERBP

This dataset contains RecID from I-CeM Adjustment Weights for the 1891-1911 England and Wales censuses and corresponds to Supplementary material for the paper "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses PI Prof. Robert J. Bennett. The material consists of three raw text files 1. 1891 Employment status & Weights 2. 1901 Employment status & Weights 3. 1911 Employment status & Weights Each file has the three following variables: 1. RecID: the ID for I-CEM2 as in Higgs, Edward and Schürer, Kevin (University of Essex) (2014) The Integrated Census Microdata (I-CeM) UKDA, SN-7481; K. Schürer, E. Higgs, A.M. Reid, E.M Garrett, Integrated Census Microdata, 1851-1911, version V. 2 (I-CeM.2), (2016) [data collection] UK Data Service SN: 7481 2. Employment status: 1 Worker 2 Employer 3 Own-account 3. Weights: the inverse of the probability of giving an answer to the Employment Status question of the censuses by Sex and Relationship to the head of the family. A detailed explanation of how these weights were calculated and how to use them in the context of data analysis of this censuses can be found in the accompanying working paper, Montebruno, Piero (2018) ‘Adjustment Weights 1891-1911: Weights to adjust entrepreneurs taking account of non-response and misallocation bias in Censuses 1891-1911’, Working Paper 11: ESRC project ES/M010953: ‘Drivers of Entrepreneurship and Small Businesses’, University of Cambridge, Department of Geography and Cambridge Group for the History of Population and Social Structure. The files can be opened by any text editor, database management system (Access) or statistical package (Stata, SPSS) This dataset should be cited as Adjustment Weights 1891-1911, "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. Please cite using its DOI.

The Census of Agriculture is conducted every 5 years with the Census of Canada. The 1871-1911 agricultural censuses for Ontario were compiled from the Census of Canada volumes by Dr. A. Michelle Edwards, University of Guelph. For current Census of Agriculture data, refer to Statistics Canada.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

CCRI Selected Published Tables Data Files: For each census from 1911-1951, a series of published volumes and tables were produced by the Dominion of Canada’s statistical agency. From those published books, the CCRI made a selection of 23 tables which contain information regarding particular topics such as: population (male and female counts), number of dwellings, households and families, as well as religion and origin of the people. For 1941, selected tables from published volumes (2 & 5) included: Population by principal origins, for census subdivisions, 1941 Population by selected religious denominations, for census subdivisions, 1941 Buildings, dwellings, households and families, showing tenure and type of dwelling, and composition of households and families, for counties, rural and urban, 1941

This aggregate-level dataset links poor relief data recorded on 1 January 1891 with several variables from corresponding 1891 census data, all at the level of the registration district (RD). Specifically, the numbers of men and women receiving indoor and outdoor relief in the ‘non-able-bodied’ category (taken as a proxy of the numbers of older-age men and women on relief) are accompanied with a series of socio-economic variables calculated from census data on the population aged 60 years and over (our definition of ‘old age’).

Thus, the dataset fulfils two objectives:

1. To start reconciling poor relief data from the House of Commons Parliamentary Papers archive with transcribed Integrated Census Microdata (I-CeM) available at the UK Data Service (UKDS).

2. To capture geographical variations in the proportion of older-age men and women on poor relief as well as in several household, occupational and migratory compositions recorded in the census, consulting data from 1891 as a pilot study in anticipation of an extended project covering all censuses from 1851-1911.

   The study of old age in history has generally had a narrow focus on welfare needs. Specific studies of the extreme poverty, or pauperism, of older people in late nineteenth-century London by Victorian contemporary Charles Booth (1840-1916) have remained remarkably influential for historical research on old age (Booth, 1894; Boyer and Schmidle, 2009). Old age is also examined through institutional care, particularly workhouse accommodation (Lievers, 2009; Ritch, 2014), while the subgroup of the elderly population that were not poor has been underexplored. However, my PhD thesis shows that pauperism was not a universal experience of old age between 1851 and 1911. Using transcribed census data for five selected counties in England and Wales, I find that pauperism was contingent upon many socio-economic factors recorded in census datasets, such as the occupational structure of older people, their living arrangements and their capacity to voluntarily retire from work based on their savings, land and capital. I find that, in some districts of the northern counties of Cheshire and the Yorkshire West Riding, the proportion of men described in the census as 'retired' and the proportion of women 'living on their own means' was greater than the respective proportions of men and women on welfare. For elderly men in particular, there were regional differences in agrarian work, where those in northern England are more likely to run smallholding 'family farms' whereas, in southern England, elderly men generally participate as agricultural labourers. I find that these differences play an important part in the likelihood of becoming pauperised, and adds to the idea of a north-south divide in old age pauperism (King, 2000). Furthermore, pauperism was predicated on the events and circumstances of people throughout their life histories and approaching their old age.

My fellowship will enable me to expand upon these findings through limited additional research that stresses an examination of the experiences of all older people in England and Wales. Old age has to be assessed more widely in relation to regional and geographical characteristics. In this way, we refine Booth's London-centric focus on the relationship between poverty and old age. My fellowship will achieve these objectives by systematically tracing the diversity of old age experiences. A pilot study will link welfare data recorded on 1 January 1891 from the House of Commons Parliamentary Papers archive with the socio-economic indicators contained in the 1891 census conducted on 5 April, all incorporated at the level of c. 650 registration districts in England and Wales. I will also visit record offices to extract data on the names of older people recorded as receiving welfare in materials related to the New Poor Law, thereby expanding on the PhD's examination of the life histories of older people.

With the key findings from my PhD presented above, I will spend my time addressing a wider audience on my research. As I will argue in blogs and webinars addressed to Age UK, the International Longevity Centre UK and History and Policy, a monolithic narrative of old age as associated with welfare dependency and gradual decline has been constructed since Booth's research in the late nineteenth century. This narrative has remained fixed through the growth of our ageing population, and the development of both old age pensions and the modern welfare state. My research alternatively uses historical censuses that reveal the economic productivity of older people in a manner that is not satisfactorily captured in present day discourse. I will also receive training on how to address my PhD to local schools, through the presentation of maps that present variations in the proportions of older people receiving welfare, and in the application of transcribed census data.

These data have been generated as part of the work being undertaken by the Kingston Local History Project. The aim of this project is to create a comprehensive database covering the people who lived, worked and died in Kingston upon Thames between 1850 and 1911. The core of the database is the census enumerators' returns for each census year between 1851 and 1891, supplemented by vital registration sources such as parish registers (baptisms, marriages and burials) and the local authority cemetery records.

Analysis of the data is providing a wealth of information on such questions as occupational structures; class profiles; household structures; demographic trends etc., and indicating how these changed over time. For example, this burial database has provided a great deal of material on mortality in Kingston between 1850 and 1911, including the age profile of mortality (in particular highlighting the high and increasing incidence of infant mortality), and the seasonality of mortality. By linking these data to other sources such as the census enumerators' books, maps and Medical Officer of Health reports, we can examine the influence of such factors as location, housing conditions, father's occupation (in the case of infants) etc. on mortality.

Aggregate data files digitized from the published census volumes for 1911. The files were downloaded from the University of Saskatchewan Historical Geographic Information Systems Lab. This data were developed as part of the The Canadian Peoples / Les populations canadiennes Project.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.