An Exploration of the Content and Usability of Web-Based Resources Used by Individuals to Find and Access Family Physicians
Bibliographic record
Abstract
Background: The most commonly recommended strategy in Canada for patients wishing to find a regular family physician (FP) is through the use of websites with FP listings. We aimed to explore the content and usability of these websites. Methods: We identified publicly available websites with FP listings in Western Canada, analyzing them thematically through open coding for website content and conducting framework analysis for website usability. Results: Twelve unique websites were identified and grouped into three categories: (1) Physician regulatory authorities ("Colleges"); (2) Governmental; and (3) Miscellaneous. College websites provided the greatest detail about the FPs and enabled searching, though had low readability. Governmental websites listed basic contact information and were credible but contained less detail than College websites. Miscellaneous websites were narrower in focus and therefore easier to navigate but lacked updated and accurate information. Conclusions: Many websites help patients find FPs. Their content and usability are variable, suggesting a need for guidance in the development of these resources.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".