3 ms·

You're moving goalposts, friend. What you're suggesting and what OP are suggesting are in two completely different categories of disclosure extent. I don't thin

by chaps 3y ago

You're moving goalposts, friend. What you're suggesting and what OP are suggesting are in two completely different categories of disclosure extent. I don't think anybody here is suggesting that no data should be available to the public.

prepend 3y ago
I don’t think so. OP was saying the data should be released. CA is saying it can’t at all for privacy reasons. I’m saying that the data OP can be released with perturbations made to protect privacy and the data are still useful. I don’t think anyone is calling for the raw data to be dumped. But for as much data as possible to be released.
- mlyle 3y ago
  I agree with the person's criticism of your comment. Yes, obviously there is a level of aggregation where privacy concerns no longer hold. But there is no trivial transformation that allows education researchers the data they need but preserves anonymity. Education researchers want to aggregate and statistically sample the data in new ways; pre-aggregating it removes most ability to do so. If you want to do a principal component analysis of a few variables-- good luck with aggregate data. If you provide nearly any data at the student-level, there's a pretty high chance that it can be deanonymized. At the same time, the state's position of attempting to prevent education researchers from participating in litigation (when using only public, non-restricted data) is egregious.
  - prepend 3y ago
    I’m talking about perturbing the micro data enough to allow researchers to answer their questions while remaining analytically valuable. For example with school attendance data you could easy release a dataset at the county level with every student’s record with unique generated student id, race, grade, gender, absences by year (or even month) and still have 5-20 of each category to be able to show attendance trends before and after Covid without being able to identify individuals. And, if necessary, suppress really unique race or gender instances (eg, maybe there’s only one trans, Native American in a school) while still being useful enough to make useful findings for general trends. I don’t know what specific questions, but the state not releasing any data to them and claiming privacy is silly. The census and department of ed already do this and the department of ed has a very useful description of how they apply privacy protections and validate that data are sufficiently anonymized for public release, https://studentprivacy.ed.gov/sites/default/files/resource_document/file/data_deidentification_terms_0.pdf https://studentprivacy.ed.gov/sites/default/files/resource_d...
    - mlyle 3y ago
      > For example with school attendance data you could easy release a dataset at the county level with every student’s record with unique generated student id, race, grade, gender, absences by year (or even month) and still have 5-20 of each category to be able to show attendance trends before and after Covid without being able to identify individuals. Yes, for any kind of specific study you want to do, you can form aggregates that support it. Indeed, lots of aggregate data is already released publicly. Lots of aggregate data is already released publicly. If you want the actual, real data, so you can answer questions like --- "what about attendance on Mondays in students receiving subsidized lunch-- what does it predict about that student's attendance in the future?" --- you'll either need the real data, or for the state to basically do your data aggregation for your specific question.

by chaps 3y ago

prepend 3y ago

I don’t think so. OP was saying the data should be released. CA is saying it can’t at all for privacy reasons. I’m saying that the data OP can be released with perturbations made to protect privacy and the data are still useful. I don’t think anyone is calling for the raw data to be dumped. But for as much data as possible to be released.

mlyle 3y ago
I agree with the person's criticism of your comment. Yes, obviously there is a level of aggregation where privacy concerns no longer hold. But there is no trivial transformation that allows education researchers the data they need but preserves anonymity. Education researchers want to aggregate and statistically sample the data in new ways; pre-aggregating it removes most ability to do so. If you want to do a principal component analysis of a few variables-- good luck with aggregate data. If you provide nearly any data at the student-level, there's a pretty high chance that it can be deanonymized. At the same time, the state's position of attempting to prevent education researchers from participating in litigation (when using only public, non-restricted data) is egregious.
- prepend 3y ago
  I’m talking about perturbing the micro data enough to allow researchers to answer their questions while remaining analytically valuable. For example with school attendance data you could easy release a dataset at the county level with every student’s record with unique generated student id, race, grade, gender, absences by year (or even month) and still have 5-20 of each category to be able to show attendance trends before and after Covid without being able to identify individuals. And, if necessary, suppress really unique race or gender instances (eg, maybe there’s only one trans, Native American in a school) while still being useful enough to make useful findings for general trends. I don’t know what specific questions, but the state not releasing any data to them and claiming privacy is silly. The census and department of ed already do this and the department of ed has a very useful description of how they apply privacy protections and validate that data are sufficiently anonymized for public release, https://studentprivacy.ed.gov/sites/default/files/resource_document/file/data_deidentification_terms_0.pdf https://studentprivacy.ed.gov/sites/default/files/resource_d...
  - mlyle 3y ago
    > For example with school attendance data you could easy release a dataset at the county level with every student’s record with unique generated student id, race, grade, gender, absences by year (or even month) and still have 5-20 of each category to be able to show attendance trends before and after Covid without being able to identify individuals. Yes, for any kind of specific study you want to do, you can form aggregates that support it. Indeed, lots of aggregate data is already released publicly. Lots of aggregate data is already released publicly. If you want the actual, real data, so you can answer questions like --- "what about attendance on Mondays in students receiving subsidized lunch-- what does it predict about that student's attendance in the future?" --- you'll either need the real data, or for the state to basically do your data aggregation for your specific question.