Does the Profit Motive Matter? COVID-19 \nPrevention and Management in Ontario \nLong-Term-Care Homes
Bibliographic record
Abstract
Dans cet article, nous présentons quelques éléments de preuve que les fournisseurs de soins de longue durée à but lucratif ont eu de moins bons résultats dans la gestion de la pandémie de la COVID-19. Nous avançons deux séries d'arguments théoriques qui prédisent la variation dans la qualité du service selon le type de fournisseur: ceux qui ont trait à l'institution contractante (concurrence novatrice versus concurrence érosive) et ceux qui s'intéressent aux caractéristiques organisationnelles des acteurs à but lucratif, sans but lucratif et gouvernementaux (recherche de profit, interfinancement et investissement futur). Nous mettons ces arguments en contexte en discutant les façons dont les contrats sont attribués dans le cas des soins de longue durée en Ontario. Cette analyse nous pousse à exclure les arguments institutionnels et à conserver, comme nos trois hypothèses, les arguments sur les caractéristiques organisationnelles. En utilisant les données relatives à l'épidémie à partir de février 2021, nous constatons que les établissements de soins de longue durée gouvernementaux ont surpassé les établissements à but lucratif et sans but lucratif dans la gestion de l'épidémie, ce qui concorde avec une conclusion antérieure par Stall et ses collègues (2020). Ces résultats concordent avec les attentes dérivées de deux arguments théoriques – la recherche du profit et l'interfinancement – mais pas avec le troisième, celui de l'investissement futur. Abstract: We introduce evidence that for-profit long-term-care providers are associated with less successful outcomes in coronavirus disease 2019 outbreak management. We introduce two sets of theoretical arguments that predict variation in service quality by provider type: those that deal with the institution of contracting (innovative competition vs. erosive competition) and those that address organizational features of for-profit, non-profit, and government actors (profit seeking, cross-subsidization, and future investment). We contextualize these arguments through a discussion of how contracting operates in Ontario long-term care. That discussion leads us to exclude the institutional arguments while retaining the arguments about organizational features as our three hypotheses. Using outbreak data as of February 2021, we find that government-run long-term-care homes surpassed for-profit and non-profit homes in outbreak management, consistent with an earlier finding from Stall et al. (2020). Non-profit homes outperform for-profit homes but are outperformed by government-run homes. These results are consistent with the expectations derived from two theoretical arguments—profit seeking and cross-subsidization—and inconsistent with a third—capacity for future investment.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".