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QUESTION

How does the Housing Vacancy Survey (HVS) integrate 311 and code enforcement data to measure housing quality?

1:31:05

·

4 min

The NYC Department of Housing Preservation and Development (HPD) integrates 311 calls and code enforcement data into the Housing Vacancy Survey (HVS) to complement direct interviews and unit observations for a comprehensive understanding of housing quality.

  • 311 and code enforcement data are merged with interview and observation data in the HVS to provide a detailed picture of housing issues.
  • This integration allows the identification of problems not reported through 311, broadening the scope of housing quality assessment.
  • The process of merging these data sets is complex and aims to protect the privacy of individuals.
  • In addition to HVS data, information from public engagement and tenant support initiatives guide future investment and enforcement strategies.
  • The complementary use of these different data sources offers a more complete view of housing quality than could be achieved through any single source alone.
Pierina Ana Sanchez
1:31:05
How does the HBS integrate 311 in violation data.
1:31:10
Does the housing quality, you know, reporting that is in the HBS integrate those numbers?
Elyzabeth Gaumer
1:31:17
It's a great question.
1:31:19
Yes.
1:31:21
We do integrate code enforcement data into the HBS on the back end.
1:31:25
So as I described before, we sort of have the heart of this is our interviews and our sampled units.
1:31:31
That are selected scientifically to represent themselves and others.
1:31:35
And then we take other data and we sort of attach it if you can think of it that way.
1:31:40
And that does include code enforcement data.
1:31:45
Full stop.
1:31:47
Our way of measuring housing quality is I think really important to understand.
1:31:55
As a compliment to code enforcement data served on their own.
1:31:58
So you can think of each of these as doing slightly different things that together give us the best current picture of housing quality for lack of a better term, mostly housing problems.
1:32:08
So code enforcement data, particularly in the aggregate, right, look, cake taking, for example, our open data and analyzing that, does obviously convey where there are code violations, right, or multi bold code violations by different type typologies of buildings.
1:32:27
But that doesn't represent all housing units.
1:32:31
Right?
1:32:32
Our code enforcement data is by definition a selection of buildings and units that are going through that process.
1:32:40
So people who have called 311 as opposed to having problem that didn't call 311 for a variety of reasons.
1:32:46
Or a building that was referred right from a community partner versus a building that didn't get flagged for whatever reason, right, by somebody to to put it in front of us.
1:32:55
Etcetera.
1:32:56
So in various ways, at AM, I will say, it also represents where someone was able to access a unit, verify the conditions, issue of violation.
1:33:07
Right?
1:33:07
There's a very long sequence of going through that process.
1:33:12
Those are incredibly important things.
1:33:14
But again, the HVS does something slightly different and complementary to that.
1:33:18
So what we do is we ask the occupants themselves.
1:33:22
Yeah.
1:33:23
And we do our own observations of conditions.
1:33:26
Right?
1:33:27
And we've done that for many, many cycles in consistent way as we can to track change over time, but we don't verify those right through our interviews.
1:33:38
We obviously have very highly trained focused field interviewers, but they are not building inspectors.
1:33:44
Right?
1:33:45
You can imagine the variety of ways.
1:33:47
Right?
1:33:48
We're also doing this at a certain period of time, usually late winter, early spring.
1:33:53
Right?
1:33:53
So all of those are a factor of of what we are measuring.
1:33:58
But we do it in a full universe way.
1:34:01
We've we reach people and they tell us, right, they report these problems who have never ever called through on one for Right?
1:34:07
We will pick them up.
1:34:09
So those two things are different.
1:34:11
We do merge in and actually look at the overlapping issues to to try to get a better picture, and we're hoping that we'll be able to share some of those data in the coming months.
1:34:21
That's a very complicated process to match all of those data together.
1:34:25
And ensure data privacy of the individuals, which is really the hardest part for us, but we are working on that.
Ahmed Tigan
1:34:31
And and I'll just add, I think this speaks to the proactive piece.
1:34:35
So we had mentioned earlier that public engagement unit and a 10 support unit, the knocking on doors, the information we get back either through the neighborhood based work or targeted days of action.
1:34:45
That plus the work that we do in the 10 harassment cabinet.
1:34:48
This information allows us to sync what the future should look like in terms of investment, in terms of strategies, how we form and even frame what our enforcement teams look like.
1:35:00
And So this all of this is used in one way or another, but they are separate datasets.
Pierina Ana Sanchez
1:35:06
Thank you.
1:35:06
And and is that process that you're undertaking now is the merging at the unit level?
1:35:13
Okay.
1:35:14
That explains why you can't release it.
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