All Outputs (7)

Spontaneous recognition: An unneccessary control on data access? (2017)
Book Chapter
Ritchie, F. (2017). Spontaneous recognition: An unneccessary control on data access?. In E. Baldacci, G. Benoist, C. Boldsen, M. Galambosne Tiszbergen, J. Gerendas, M. Karlberg, …Z. Vereczkei (Eds.), Selected papers from the 2016 Conference of European Statistics Stakeholders (148-158). Luxembourg: Publications Office of the European Union. https://doi.org/10.2785/091435

Social scientists increasingly expect to have access to detailed source microdata for research purposes. As the level of detail increases, data owners worry about ‘spontaneous recognition’, the likelihood that a microdata user believes that he or she... Read More about Spontaneous recognition: An unneccessary control on data access?.

Open data: Who needs it? (2017)
Presentation / Conference
Ritchie, F. (2017, September). Open data: Who needs it?. Presented at UNECE/Eurostat work session on statistical data confidentiality - 2017, Skopje, FYR Macedonia

This presentation, to introduce and stimulate a panel discussion, argued that we have 50 years worth of experience in knowing how to use data safely for researcher; as such we should be concentrating on practical management problems not theory: "how-... Read More about Open data: Who needs it?.

Lessons learned in training ‘safe users’ of confidential data (2017)
Presentation / Conference
Ritchie, F., Green, E., Newman, J., & Parker, T. (2017, September). Lessons learned in training ‘safe users’ of confidential data. Paper presented at UNECE/Eurostat work session on statistical data confidentiality - 2017, Skopje, FYR Macedonia

Many statistical organisations require researchers using detailed sensitive data to undergo ‘safe researcher’ training. Such training has traditionally reflected the ‘policing’ model of data protection. This mirrors the defensive stance often adopted... Read More about Lessons learned in training ‘safe users’ of confidential data.

The "Five Safes": A framework for planning, designing and evaluating data access solutions (2017)
Presentation / Conference
Ritchie, F. (2017, September). The "Five Safes": A framework for planning, designing and evaluating data access solutions. Paper presented at Data for Policy 2017, London, UK

The ‘Five Safes’ is a popular way to structure thinking about data access solutions. Originally used mainly by statistical agencies and social science academics , in recent years it has been adopted more widely across government, health organisations... Read More about The "Five Safes": A framework for planning, designing and evaluating data access solutions.

Spontaneous recognition: An unnecessary control on data access? (2017)
Journal Article
Ritchie, F. (2017). Spontaneous recognition: An unnecessary control on data access?. https://doi.org/10.2866/430525

Social scientists increasingly expect to have access to detailed data for research purposes. As the level of detail increases, data providers worry about “spontaneous recognition”, the likelihood that a microdata user believes that he or she has acci... Read More about Spontaneous recognition: An unnecessary control on data access?.

Ensuring the confidentiality of statistical outputs from the ADRN (2017)
Report
from the ADRN

This technical report discusses potential risks to confidentiality from publication of statistical results based on confidential data, and what we can do to minimise that risk while still ensuring that useful research gets published.

Measuring compliance with minimum wages (2017)
Journal Article
Ritchie, F., Veliziotis, M., Drew, H., & Whittard, D. (2017). Measuring compliance with minimum wages. Journal of Economic and Social Measurement, 42(3-4), 249-270. https://doi.org/10.3233/JEM-180448

© 2017 - IOS Press and the authors. All rights reserved. Identifying genuine underpayment of minimum wages is not straightforward. Some well-known statistical issues affect the measurement of compliance rates, but factors such as processing or behavi... Read More about Measuring compliance with minimum wages.