‘I cannot be passive as I was before’: learning from grassroots innovations in Ukraine
Bibliographic record
Abstract
The study explores learning processes and outcomes inside grassroots innovations that are emerging in post-Euromaidan times in Ukraine. The study analyses the assumption that this non-traditional education space can be adequate for sustainability transition learning and critical consciousness development. First, the study describes, connects, and operationalizes the concepts of critical consciousness, sustainability transition, and grassroots innovations. Then, it analyses two cases of grassroots innovations (two online sharing platforms), using these operationalized concepts. The results show that learning and critical consciousness development inside grassroots niches are much more connected to previous experience, such as participation in the protest event Euromaidan, than to inner niche learning interactions. While, the online platforms keep alive some of the aspirations that motivated people to become a part of the Euromaidan protest. In this sense, such grassroots innovations keep the values and priorities of the participants “alive” and ensure that the critical consciousness that was acquired does not simply slide backwards. Do shocking events like Euromaidan protest have to happen in order to accelerate learning about values of solidarity and responsibility, as well as to develop critical consciousness needed for sustainability transition? Despite the impossibility to completely answer this question, this study gave some tips, suggesting components of critical conscious development needed for this type of learning¾dialog, reflection, action, leading to increase in efficacy and agency.
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How this classification was reachedexpand
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 | 0.004 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".