The effects of race and criminal history on landlords’ (un)willingness to rent to exonerees.
Bibliographic record
Abstract
OBJECTIVE: When wrongfully convicted individuals are released from prison, at first glance, it is a triumph; however, anecdotal evidence from exonerees suggests that obtaining housing postrelease is often challenging. We empirically examined whether race (Study 1) or type of criminal offense (Study 2) influenced landlords' willingness to rent to exonerees compared to releasees (i.e., rightfully convicted individuals released from prison) and control (i.e., members of the public). HYPOTHESES: We hypothesized that: (a) exonerees and releasees would receive fewer replies and fewer "yes" available responses compared to control, (b) Indigenous and Black renters would receive fewer replies and fewer "yes" available responses compared to White renters, and (c) individuals convicted of murder would receive fewer replies and fewer "yes" available responses compared to individuals convicted of robbery. METHOD: The authors responded to online apartment listings across Canada (Study 1) and in Toronto (Study 2) inquiring about unit availability. All rental inquiries were identical with the exception of criminal status and race (Study 1), and criminal status and criminal offense (Study 2). RESULTS: Results demonstrated that landlords were significantly less likely to respond (Study 1: OR = 4.32, 95% CI [3.28, 5.69]; Study 2: OR = 7.88, 95% CI [4.97, 12.48]), and indicate availability (Study 1: OR = 6.62, 95% CI [3.54, 12.38]; Study 2: OR = 21.53, 95% CI [7.07, 65.58]), to rental inquiries from exonerees and releasees compared to members of the public. For race, landlords were significantly less likely to respond to inquiries from Indigenous and Black renters compared to White renters (OR = 1.45, 95% CI [1.12, 1.86]), and those convicted of robbery compared to murder (OR = 1.69, 95% CI [.36, .97]). CONCLUSION: The barriers that exonerees face when attempting to secure housing postrelease are potentially as great as those facing releasees; however, exonerees do not receive assistance with reentry. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".