Data on Vietnamese patients׳ behavior in using information sources, perceived data sufficiency and (non)optimal choice of health care provider
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This data article introduces a data set containing 1459 observations that can enable researchers to examine issues related to and perform statistical investigations into questions of relationships between sources of health care information, data sufficiency, trust levels between patients and healthcare experts (and the advice). The data set also records assessment of Vietnamese patients on whether their choice of health care provider is best available (optimal vs. nonoptimal). The data come from a survey in many hospitals in Hanoi and several neighboring provinces/cities in the North of Vietnam, during the last quarter of 2015. Variables that can be useful for future analysis include sources and availability of information, cost, and amount of time for seeking information. The quality of information and health professionals' credibility are critical factors in helping patients choose a health care provider. Mendeley Data, v1 http://dx.doi.org/10.17632/gmbz53tpwc.1; and can enable the modeling after useful discrete data models such as BCL, with one example being provided in this data article.
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.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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 it