All Outputs (125)

10 is the safest number that there's ever been (2022)
Journal Article
Ritchie, F. (2022). 10 is the safest number that there's ever been. Transactions on data privacy, 15(2), 109-140

When checking frequency and magnitude tables for disclosure risk, the cell threshold (the minimum number of observations in each cell) is a crucial parameter. In rules-based environments, this is a hard limit on what can or can't be published. In pri... Read More about 10 is the safest number that there's ever been.

Enriched ASHE Quick Start Guide (2022)
Working Paper
Whittard, D., Ritchie, F., Stokes, L., Forth, J., Phan, V., Bryson, A., & Singleton, C. Enriched ASHE Quick Start Guide

The Wage and Employment Dynamics (WED) project was funded by Administrative Data Research 2019-2022 to review, quality assure and enhance ASHE data. The project was also provided with ASHE data linked to the 2011 Census for England and Wales. This do... Read More about Enriched ASHE Quick Start Guide.

A marriage of convenience: How employers and students working in hospitality view the employment relationship (2022)
Journal Article
Evans, C., Ritchie, C., Drew, H., & Ritchie, F. (2022). A marriage of convenience: How employers and students working in hospitality view the employment relationship. Hospitality and Society, 12(3), 299-318. https://doi.org/10.1386/hosp_00055_1

Since the 1990s, the hospitality industry has been increasingly characterized by temporary and insecure forms of employment, a development, which has coincided with rising numbers of students seeking part-time employment. This provides increased job... Read More about A marriage of convenience: How employers and students working in hospitality view the employment relationship.

Weighting for employer non-response in ASHE (2022)
Working Paper
Stokes, L., Forth, J., Ritchie, F., Singleton, C., Phan, V., Bryson, A., …McKenzie, A. Weighting for employer non-response in ASHE

The Annual Survey of Hours and Earnings (ASHE) is based on a 1% sample of employee jobs and provides many of the UK’s official earnings statistics. Weights are provided with the core dataset, which adjust the profile of the annual achieved sample suc... Read More about Weighting for employer non-response in ASHE.

Accounting for firms in ethnicity wage gaps throughout the earnings distribution (2022)
Working Paper
Phan, V., Singleton, C., Bryson, A., Forth, J., Ritchie, F., Stokes, L., & Whittard, D. (2022). Accounting for firms in ethnicity wage gaps throughout the earnings distribution

Ethnicity wage gaps in Great Britain are large and have persisted over time. Previous studies of these gaps have been almost exclusively confined to analyses of household data, so they could not account for the role played by individual employers, de... Read More about Accounting for firms in ethnicity wage gaps throughout the earnings distribution.

Disclosure risks in odds ratios and logistic regression (2022)
Presentation / Conference
Derrick, B., Green, E., Ritchie, F., & White, P. (2022, April). Disclosure risks in odds ratios and logistic regression. Paper presented at Scottish Economic Society Annual Conference 2022: Special session 'Protecting confidentiality in social science research outputs', Glasgow

When publishing statistics from confidential data, there exists a risk that the statistic might inadvertently reveal confidential information. Statistical disclosure control (SDC) aims to reduce that risk to an acceptable level. Most SDC theory is co... Read More about Disclosure risks in odds ratios and logistic regression.

Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation (2022)
Presentation / Conference
Derrick, B., Green, E., Kember, K., Ritchie, F., & White, P. (2022, April). Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation. Paper presented at Scottish Economic Society, Glasgow

Reporting the sample mean, sample standard deviation and sample size could in some cases lead to the unique identification of the underpinning sample. The likelihood of this reveal via direct enumeration of the possible search space decreases with i... Read More about Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation.

ASHE – 2011 Census Data Linkage: User Guide Drop 1 of the ASHE – 2011 Census Dataset (2022)
Working Paper
Forth, J., Phan, V., Ritchie, F., Whittard, D., Stokes, L., Bryson, A., & Singleton, C. ASHE – 2011 Census Data Linkage: User Guide Drop 1 of the ASHE – 2011 Census Dataset

Longitudinal attrition in ASHE (2022)
Working Paper
Forth, J., Phan, V., Stokes, L., Bryson, A., Ritchie, F., Whittard, D., & Singleton, C. Longitudinal attrition in ASHE

The Annual Survey of Hours and Earnings (ASHE) provides many of the UK’s official earnings statistics. The survey operates on an annual 1% sample of employee jobs. However, the method of sampling - based on the final two digits of an employee’s Natio... Read More about Longitudinal attrition in ASHE.

Training analysts in the management of confidential data (2022)
Working Paper
Green, E., & Ritchie, F. Training analysts in the management of confidential data

With researchers increasingly gaining access to confidentiality data through restricted environments, interest has grown in the training of those researchers to protect confidentiality and to use the secure facility effectively. Researcher training,... Read More about Training analysts in the management of confidential data.

Using the ‘five safes’ to structure economic evaluations of data governance (2022)
Working Paper
Ritchie, F., & Whittard, D. Using the ‘five safes’ to structure economic evaluations of data governance

The ‘five safes’ is a popular data governance framework. It is used to design and critique data management strategies across the world, and has also been used as a performance framework to measure the effectiveness of data access operations. We repor... Read More about Using the ‘five safes’ to structure economic evaluations of data governance.

Measuring the value of data governance in agricultural investments: A case study (2022)
Journal Article
Whittard, D., Ritchie, F., Rose, M., & Musker, R. (2022). Measuring the value of data governance in agricultural investments: A case study. Experimental Agriculture, 58, Article e8. https://doi.org/10.1017/S0014479721000314

Summary The study at hand measures the value of improving data governance and access in the Supporting Soil Health Interventions (SSHI) project in Ethiopia. We applied two separate but interlinked models, one qualitative and one quantitative, to crea... Read More about Measuring the value of data governance in agricultural investments: A case study.

Exploring the workplace location problem in the Annual Survey of Hours and Earnings (2022)
Working Paper
Whittard, D., Ritchie, F., Phan, V., Forth, J., Bryson, A., Stokes, L., …McKenzie, A. Exploring the workplace location problem in the Annual Survey of Hours and Earnings

The Annual Survey of Hours and Earnings (ASHE) is an important source of longitudinal linked employer-employee payroll earnings data for Britain. It provides accurate information on employees’ hours and earnings and information on the location of em... Read More about Exploring the workplace location problem in the Annual Survey of Hours and Earnings.

Statistical disclosure control for HESA: Part 1: Review of SDC theory (2021)
Report
Green, E., & Ritchie, F. (2021). Statistical disclosure control for HESA: Part 1: Review of SDC theory. Higher Education Statistics Agency (HESA)

This report for the Higher Education Statistics Agency (HESA) is a summary of statistical disclosure control (SDC) methods for tabular outputs.

Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks (2021)
Journal Article
Green, E., Ritchie, F., & Smith, J. (2021). Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks. ESS Statistical Working Papers, 2021 Edition, https://doi.org/10.2785/75954

This paper discusses the issues surrounding the creation of an automatic tool to reduce the burden of output checking in research environments. It describes ACRO (Automatic Checking of Research Outputs), a Stata tool written as a proof-of-concept, an... Read More about Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks.

Statistical disclosure controls for machine learning models (2021)
Conference Proceeding
Krueger, S., Mansouri-Benssassi, E., Ritchie, F., & Smith, J. (2021). Statistical disclosure controls for machine learning models

Artificial Intelligence (AI) models are trained on large datasets. Where the training data is sensitive, the data holders need to consider risks posed by access to the training data and risks posed by the models that are released. The first problem c... Read More about Statistical disclosure controls for machine learning models.

The present and future of confidential microdata access: Post-workshop report (2021)
Presentation / Conference
Green, E., Ritchie, F., Tava, F., Ashford, W., & Ferrer Breda, P. (2021, July). The present and future of confidential microdata access: Post-workshop report. Presented at The Present and Future of Microdata Access

In the summer of 2021, the University of the West of England, in collaboration with UN Economic Commission for Europe, Eurostat, INXEDA and statistical organisations across the world, hosted a workshop to review lessons learnt in microdata access ove... Read More about The present and future of confidential microdata access: Post-workshop report.

The present and future of confidential microdata access [draft] (2021)
Presentation / Conference
Green, E., & Ritchie, F. (2021, July). The present and future of confidential microdata access [draft]. Presented at The Present and Future of Microdata Access

This briefing document was prepared for the DRAGoN conference 'The Present and Future of Microdata Access', 5th-9th July 2021. It provides an introduction to the topics to be covered in the conference.

Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects (2021)
Journal Article
Whittard, D., Ritchie, F., & Nyengani, J. (2021). Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects. Gates Open Research, 5, Article 97. https://doi.org/10.21955/gatesopenres.1116786.1

The Centre for Agriculture and Bioscience International (CABI) and the Open Data Institute (ODI) commissioned a team of economists to measure the value of improving data governance and access in the Supporting Soil Health Interventions in Ethiopia (S... Read More about Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects.

Sequential mixed methods research: Non-compliance in apprentice pay with owls (2021)
Presentation / Conference
Drew, H., & Ritchie, F. (2021, June). Sequential mixed methods research: Non-compliance in apprentice pay with owls. Paper presented at 20th European Conference on Research Methodology for Business and Management Studies, University of Aveiro, Portugal

Within mixed methods literature, the relationship between qualitative and quantitative data collection is ubiquitously presented as sequential. Thus, the most followed approach is for the first stage of data collection to follow the second, or to run... Read More about Sequential mixed methods research: Non-compliance in apprentice pay with owls.