[Air-L] Anonymizing qual interview data?

Fri Apr 9 06:43:27 PDT 2021

   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 at gmail.com>
     Sent by: "Air-L" <air-l-bounces at listserv.aoir.org>
     To: Cory Robinson <cory.robinson at liu.se>
     Cc: "air-l at listserv.aoir.org" <air-l at 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 Ã s 05:16, Philip Derham <
   derhamp at 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 at 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 at liu.se<mailto:
   > cory.robinson at liu.se>> wrote:
   > HI all,
   >
   > Two Masterâs 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). â¹
   >
   > 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. (Itâs indeed a failure
   of
   > universities, as well as unequipped supervisors!)
   >
   > Best,
   > Cory
   >
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References

   1. https://www.esomar.org/uploads/public/knowledge-and-standards/codes-and-guidelines/ICCESOMAR_Code_English_.pdf
   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/