Building reciprocity: the dialectic processes of creating a grounded theory and the emergence of a theoretical framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it