Collective mindfulness within a food security non-profit organization during the COVID-19 crisis : a case study
Bibliographic record
Abstract
This study focussed on how collective mindfulness contributes to resilience in non-profit organizations coping with crises, such as the COVID-19 pandemic. Taking a Vancouver B.C. non-profit organization’s emergency food security response as a case study, it examines the role that mindfulness plays in non-profit organizations’ adaptations to the COVID-19 pandemic through the lens of complexity science. Specifically, it identifies emergent mindfulness processes and their effects on organizational resilience within non-profit organizations. This qualitative research employs a responsive, phronetic-iterative approach to interviewing and analysis that is grounded in a post-structuralist paradigm; attempts to advance a complexity-based theory of collective mindfulness; and furthers complexity science as a comprehensive interpretive framework. Findings demonstrate that collective mindfulness may be enacted through interdependent processes of dynamic reflexivity, responsive self-organization, and flexible co-evolution, through which resilience may emerge.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".