Tracing the Link Between Transformative Education and Social Action Through Stories of Change
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
The following article describes how one organization, the Coady International Institute, met multiple monitoring, evaluation, research, and learning objectives while still staying true to its roots in transformative adult education. The Learning from Stories of Change (LSC) methodology brought together stories-based techniques with aspects of the Most Significant Change and the SenseMaker frameworks. The combination of methods was designed to facilitate reflection and a degree of participatory analysis in an online environment that reached over 400 graduates in 64 countries. It produced a rich set of data that provided key insights into program design and confirmed the transformative adult education model—particularly, that increases in knowledge and skills must be accompanied by changes in attitudes and motivations in order to make the leap from concepts to practice. This leads to individual behavioral changes that will in turn initiate positive social change in communities around the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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