Field Notes and Theoretical Memos in Grounded Theory
Bibliographic record
Abstract
In this article the authors expose some of the mystique surrounding field notes and theoretical memos in a Glaserian grounded theory study. Definitions, types, and content of field notes and theoretical memos are presented. Exemplars from a study of mothers living with serious mental illness are provided to illustrate how these forms of documentation evolved during the course of the study. The authors argue that, although the processes of field noting and memoing may blur as a study progresses, they nevertheless retain their independent functions. The authors contend that without understanding the complementary function of these two types of documentation, data cannot evolve to a higher interpretive level. This article contributes specific ideas for improving the methods used by qualitative nurse researchers.
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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 | 0.145 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.010 | 0.124 |
| Scholarly communication | 0.016 | 0.031 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".