Bibliographic record
Abstract
Property maintenance affects health and safety, market values and neighbourhood dynamics. Previous studies have indicated that owner-occupiers maintain their properties better than do absentee (non-resident) landlords. Some evidence suggests that maintenance by resident landlords falls in between but no study has compared all three tenures. This study of the City of Rochester, New York, utilises tax data for every residential property in the city in 2017, these being linked to records of building inspections, mostly pro-active. It indicates that code violations were highest for absentee-owned properties, lowest for the owner-occupied and intermediate for the properties of resident landlords. Comparison of the two- and three-unit properties of resident landlords indicates the impact of pro-active inspections. Maintenance by Limited Liability Companies was about average for absentee-owned properties, but those handled by management companies were worse. Longitudinal analysis of independent changes in the ownership and tenure of dwelling units, 2011–2017, indicates that observed differences in maintenance in 2017 were attributable to the incentives characteristic of each tenure, not to differences in personal preference among property owners. Results underline the importance of pro-active inspections and the need for qualitative research to clarify the motivations of different types of landlords.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".