Preregistering Qualitative Research: A Delphi Study
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
Preregistrations—records made a priori about study designs and analysis plans and placed in open repositories—are thought to strengthen the credibility and transparency of research. Different authors have put forth arguments in favor of introducing this practice in qualitative research and made suggestions for what to include in a qualitative preregistration form. The goal of this study was to gauge and understand what parts of preregistration templates qualitative researchers would find helpful and informative. We used an online Delphi study design consisting of two rounds with feedback reports in between. In total, 48 researchers participated (response rate: 16%). In round 1, panelists considered 14 proposed items relevant to include in the preregistration form, but two items had relevance scores just below our predefined criterion (68%) with mixed argument and were put forth again. We combined items where possible, leading to 11 revised items. In round 2, panelists agreed on including the two remaining items. Panelists also converged on suggested terminology and elaborations, except for two terms for which they provided clear arguments. The result is an agreement-based form for the preregistration of qualitative studies that consists of 13 items. The form will be made available as a registration option on Open Science Framework (osf.io). We believe it is important to assure that the strength of qualitative research, which is its flexibility to adapt, adjust and respond, is not lost in preregistration. The preregistration should provide a systematic starting point.
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 | 0.110 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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