I think part of the thinking-process might be: How easily can someone figure out the identity of the informant? If I were to say that I interviewed people in our 8-person team, and if I report that one person was working from the Pacific timezone, then it's easy to determine which of us I am referring to. Or if I were to write that a disabled member of the team said... then that's me. I know that seems obvious for a tiny group, but these kinds of intersectional identities can operate in larger groups, too. A second way-of-thinking may involve a focus on the risk of disclosure to the informant. However, this criterion often becomes a matter of the researcher's imagination regarding the Other. It's been shown again and again that people in a position of privilege and safety may not understand the very real risks that are experienced by people who have fewer safeguards - e.g., men writing about women's safety (how easily can a stalker act on the information?), or straight people writing about risk of identification of someone in one of the LGBTQIA+ spectra, or citizens making assumptions about legal protections (or lack of protections) for non-citizens. Of course, it's a good idea to discuss these matters with people who are not ourselves, and who are not like ourselves. It's also a good idea not to put the burden of explaining bias on the person who is the target of that bias. Yes, I know that I said two things that somewhat contradict each other. There are no easy answers here. A third possibility is to ask each informant to state what information about themself would be safe to share. This is sensible only if the informants understand publications and readerships, etc. But it may be a more radically democratic approach to demographic description. I'm suggesting these ideas as among a larger number of *starting points* for thinking about difficult research questions. Please think of them as heuristic questions - not as authoritative questions, and certainly not as answers! best wishes, --michael ----- Michael Muller, PhD, IBM Research, Cambridge MA USA pronouns: he/him/his ACM Distinguished Scientist ACM SIGCHI Academy ----- Original message ----- From: Josir Gomes <josircg@gmail.com> Sent by: "Air-L" <air-l-bounces@listserv.aoir.org> To: Cory Robinson <cory.robinson@liu.se> Cc: "air-l@listserv.aoir.org" <air-l@listserv.aoir.org> Subject: [EXTERNAL] Re: [Air-L] Anonymizing qual interview data? Date: Fri, Apr 9, 2021 08:58 Hi Cory, The best way that I know is to create a randomic code for each respondent and remove any timestamp that indicates the order the response was given. You can use the spreadsheet random() function to do that. It is ideal that it be random, just to increase confidentiality a bit, in case the answers' sequential order might identify the respondent in some way. About your concern to "reidentify" if research data was obtained: if someone has the original research data, she/he will always have the means to identify the original respondents, no matter the method you use to anonymize. Good luck on your research! Josir Em sex., 9 de abr. de 2021 � s 05:16, Philip Derham < derhamp@derhamresearch.com.au> escreveu:
Hi Cory,
Market researchers have much the same concern about keeping private all that is disclosed by research participants.
Possibly their rules may be of some assistance - at least to formulate some standards for the students? FYC,
[1]https://www.esomar.org/uploads/public/knowledge-and-standards/codes- and-guidelines/ICCESOMAR_Code_English_.pdf
With best wishes,
Philip Derham, DIRECTOR.
Email: derhamp@derhamresearch.com.au Web: www.derhamresearch.com.au Telephone: (61) 0414 543 765 Latest post: Office: [2]https://tinyurl.com/better-staff-performance 6 Everton Grove, SURREY HILLS, VIC. AU., 3127 Skype: philipderhamdmr Facebook: www.facebook.com/DerhamInsightsResearch Twitter: www.twitter.com/betterresponses LinkedIn: [3]https://au.linkedin.com/in/philipderham/ YouTube: Mail: Philip Derham (Derham Insights Research) PO Box 51, SURREY HILLS, VICTORIA, AU., 3127
On Wed, Apr 7, 2021 at 3:47 AM Cory Robinson
<cory.robinson@liu.se<mailto:
cory.robinson@liu.se>> wrote: HI all,
Two Master�s students I recently met are conducting recorded interviews resulting in texts they will code and quote within their theses. I have given input about how to protect the recorded interviews (encrypted, password protected, not stored in the cloud). I do not work with qual data, so I need help recommending methodology or help for anonymizing quotes in their thesis.
(I am inquiring about this for a student, that unfortunately, has not received helpful advice from their supervisor). �
The students assumed they would assign each participating an identification number, and then attribute the quote and ID # in their thesis. However, I feel there is surely a better way to ensure anonymity? (Too easy to reidentify if research data was obtained).
What methods do you utilize for anonymizing individual interview data? Or manuscripts/books helpful for this? Sadly, the students are nearing the end of the study, but late is better than never. (It�s indeed a failure of universities, as well as unequipped supervisors!)
Best, Cory
_______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers [4]http://aoir.org Subscribe, change options or unsubscribe at: [5]http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: [6]http://www.aoir.org/ References 1. https://www.esomar.org/uploads/public/knowledge-and-standards/codes-and-guid... 2. https://tinyurl.com/better-staff-performance 3. https://au.linkedin.com/in/philipderham/ 4. http://aoir.org/ 5. http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org 6. http://www.aoir.org/