For example, likely undocumented immigrants are less likely to be first degree murderers than are citizens per the ADOC data, which is just the opposite of what the report claims...
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As another example, likely undocumented immigrants are less likely to be gang members than are citizens per the ADOC data, also contra the report...
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These are just some examples, as the entire report needs to be reexamined...
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I’ve reached out to
@JohnRLottJr, but he hasn’t responded. I welcome all who are interested in this important topic to dig into the data…2 replies 0 retweets 5 likesShow this thread -
Replying to @TomWongPhD
Dear Tom: I have no email from you. I just double checked a 1 ago. When did you email me? If you have something that u want to send to me, pls do. johnrlott@crimeresearch.org As to ur 1st comment, yes people go through the system multiple times. Recidivism is discussed at length.
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Replying to @JohnRLottJr
Thanks, John. I'll resend the email now. The dataset is fascinating. Given the timeliness of the issue, we want to get this right
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Replying to @TomWongPhD @JohnRLottJr
Email sent again, looking forward to discussing. Per the data, there are 464,461 rows, but 257,058 unique "IDNOs." This makes it important to collapse the data on "IDNO." One person can commit multiple crimes, but one person can't be two gang members
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Replying to @TomWongPhD
Is the Q really how many crimes do these people commit or have they ever been to prison? I think the former. But given high rate of recidivism by citizens as we show in the paper, that means a lot larger percentage of illegal population committing crime. See Hispanic not US bornpic.twitter.com/OQSy8OZhe0
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Replying to @JohnRLottJr
Because the characteristics of those in the dataset are of great consequence, analyzing all rows without collapsing (and one can easily collapse and sum over crimes) leads to a distorted view of the population of interest...
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Replying to @TomWongPhD @JohnRLottJr
... and this doesn't yet address the noise in the citizen variable
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... the "by individual" table above provides an example. How does it account for inconsistencies in the "citizen" variable, wherein one "IDNO" can be coded citizen and noncitizen at two different points in time?
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