Negotiating With Helping Systems: An Example of Grounded Theory Evolving Through Emergent Fit
Bibliographic record
Abstract
A strength of substantive grounded theories is that they are modifiable. Yet, little attention is given in the research literature to the evolution of grounded theories through the process of emergent fit. In this article, emergent fit is discussed, and the evolution of the theoretical understanding of relationships with helping systems is provided as an example. In a feminist grounded-theory study of women's caring, emergent fit with existing inductive research on health care relationships resulted in a framework of negotiating, which includes four strategies: reframing responsibility, becoming an expert, harnessing resources, and taking on more. This explanatory model demonstrates how the use of emergent fit can avoid the generation of isolated theories and contribute to knowledge accumulation by producing a substantive theory with wider applicability.
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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 | 0.038 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| 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".