Bibliographic record
Abstract
The authors of the paper, "The Patient Experience in Ontario 2020: What is Possible?", framed both the current state as well as the future of what patient experience might look like in five years. To ensure intention is catalyzed into meaningful change to improve experience and outcomes, we suggest four winning conditions. The first is to change the language; patients are people too, irrespective of their disease or illness; person-centred is inclusive language and ought to be the focus. The second condition is focused on leaders who play a critical role to establish, build and embed person-centred within the organization. The third and fourth winning conditions are building the evidence base and using effective and meaningful engagement, moving beyond advice, to partnership, respectively. Person-centred care is not the flavour of the month, it is here to stay. Ontarians are important actors in the system not only as users of the system but owners as well. To those who might argue that it is costly to do this work, what are the costs to not engage? Are we satisfied not only as administrators, and clinicians, but as patients at some point, to maintain the status quo?
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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.007 |
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".