Building reciprocity: the dialectic processes of creating a grounded theory and the emergence of a theoretical framework
Bibliographic record
Abstract
We reflect on and illustrate with concrete examples the various systematic and creative steps taken along the process of grounded theory (GT). This process led to the emergence of a theoretical framework centered on building reciprocity as a way of collaborating with socio-economically disadvantaged communities and a means for facilitating poverty-reduction initiatives. This article aims to present the systematic processes of analysis that lie behind the theoretical framework and to reflect on the lessons learned along the path to creating a GT. In this way, the emergence of the theoretical framework is examined along the different inductive and analytic steps, and the interrelation between concepts is discussed. Theoretical sensitivity, pacing, sampling, coding, memoing, and sorting in this research are illustrated and brought to light.
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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 | 0.309 | 0.184 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.013 | 0.099 |
| Scholarly communication | 0.022 | 0.024 |
| Open science | 0.007 | 0.022 |
| Research integrity | 0.006 | 0.014 |
| 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".