Enhancing the Rigor of Grounded Theory: Incorporating Reflexivity and Relationality
Bibliographic record
Abstract
Some proponents of the grounded theory method appear to treat interview and participant observation data as though they mirror informants' realities. Others claim that grounded theory incorporates reflexivity. It is claimed in this article that the principal texts on grounded theory do not attend to the effects of interactions between researchers and participants in interview and participant observation contexts. Descriptions of the effects of interactions on interview data and attention to relationships between interviewers and interviewees are necessary for attending to the rigor of grounded theory findings. Therefore, it is argued that reflexivity and relationality, which are defined as attending to the effects of researcher-participant interactions on the construction of data and to power and trust relationships between researchers and participants, should be incorporated into grounded theory.
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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 | 0.643 | 0.669 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.007 | 0.045 |
| Scholarly communication | 0.022 | 0.025 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".