[Quantitative and qualitative research methods, can they coexist yet?].
Bibliographic record
Abstract
Qualitative design is gaining ground in Nursing research. In spite of a relative progress however, the evidence based practice movement continues to dominate and to underline the exclusive value of quantitative design (particularly that of randomized clinical trials) for clinical decision making. In the actual context convenient to those in power making utilitarian decisions on one hand, and facing nursing criticism of the establishment in favor of qualitative research on the other hand, it is difficult to chose a practical and ethical path that values the nursing role within the health care system, keeping us committed to quality care and maintaining researcher's integrity. Both qualitative and quantitative methods have advantages and disadvantages, and clearly, none of them can, by itself, capture, describe and explain reality adequately. Therefore, a balance between the two methods is needed. Researchers bare responsibility to society and science, and they should opt for the appropriate design susceptible to answering the research question, not promote the design favored by the research funding distributors.
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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 | 0.333 | 0.380 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".