Does the Profit Motive Matter? COVID-19 Prevention and Management in Ontario Long-Term-Care Homes
Bibliographic record
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.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".