‘Emergent reconstruction’ in grounded theory: learning from team-based interview research
Bibliographic record
Abstract
Constructivist grounded theory (CGT) methods render an interpretive portrayal, a construction of reality, strengthened when the process of construction is acknowledged. An Irish team study uses CGT to explore intergenerational solidarity at individual, familial and societal levels, and their interface. The study data comprise interviews with 100 people from diverse socio-economic and age groups. The article contributes insights on applying CGT in team-based interview research on a topic with such breadth of scope. This contrasts with the more usual focused inquiry with a defined population. Adapting the method’s guidelines to the specific inquiry involved challenges in: framing the topic conceptually; situating research participants in contrasting social contexts to provide interpretive depth; and generating interview data with which to construct theory. We argue that interrogating the very premise of the inquiry allowed for emergent reconstruction, a goal at the heart of the method.
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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 | 0.120 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.003 | 0.007 |
| 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".