Considerations for making informed choices about engaging in open qualitative research
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
There is currently little guidance that exists for researchers in the sport and exercise sciences on open qualitative research practices. The purpose of paper is to provide researchers with guidance regarding the considerations necessary for making informed decisions about engaging in open research practices within qualitative inquiry. The guidance was developed through a series of four working group meetings with experts in qualitative research and meetings with key stakeholders (study participants, journal editors, and data management experts). The wider open qualitative research literature also informed the guidance. Nine core values were first identified as underpinning the considerations for engaging in open qualitative research practices: Choice (academic freedom and participant autonomy); Plurality not replication; Flexibility and emergent design; Transparency; Relational ethics; Quality; Education; Equity; and Responsibility. Considerations for researchers are then provided in the following areas as they pertain to open science practices in qualitative inquiry: Types of Data; Types of Studies; Participant Groups; Anonymity and Confidentiality; Participant Consent; Storage and Stewardship of Qualitative Data; Knowledge Dissemination and Open Access Publications; Cost, Time, and Resources; and Preregistration of Qualitative Studies. This paper provides an initial framework for identifying considerations for engaging in open qualitative research practices. These considerations will help qualitative researchers make informed decisions about and plan for implementation of open science practices, as well as assessing the risks and benefits of open science practices in qualitative inquiry.
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 | 0.104 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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