Reordering our Priorities through Systems Change Learning
Bibliographic record
Abstract
This workshop is online with parallel breakout groups. \n \nThe idea of “systems change” has risen in popularity over the past few years. To make this more than just another buzzword, how might we approach it? In what ways does “systems change” mean more than just “change”? Does “systems change” build on the large legacy of “systems thinking”? \n \nThe Systems Changes Learning Circle is now in year two of a 10-year journey. Our aim is to reify systems changes as a first-class concept. This extends prior published research on social and organizational change, based in the systems sciences. At RSD8, the Khan and Ing (2019) presentation reflected the early explorations coming from the core group. For RSD9 this extends to a workshop to share some methods in the early stages of development for initiating deeper deliberations into systems changes. \n \nSystems changes may involve: \n \n• shifting adaptively; \n• shifting behaviorally, and/or \n• shifting ecologically. \n \nLiving systems may respond through: \n \n• systematic changes; \n• systemic changes; and/or \n• timescape-landscape changes. \n \nDegrees of systems changes may be judged as: \n \n• unfolding nature; \n• fixing problems; or \n• history-making. \n \nThe multi-day, iterative workshop still under development takes a multi-paradigm approach based on learnings grounded in five philosophies: \n \n(i) learning which, as phenomenology; \n(ii) learning what, as ontology; \n(iii) learning why, as epistemology; \n(iv) learning whom+when+where, as phronesis; and \n(v) learning how, as techne. \n \nTo convene working groups in advance of iterations on the five learnings, Khan and Ing propose a Question Zero conversation for orientation, on Reordering Priorities. \n \nThe workshop is structured as multiple steps: \n \nStep 0: Participants will introduce themselves briefly. To encourage discussion, participants will be encouraged to cluster into small groups with others whom they do not know well. \n \nStep 1: As individuals, participants will each quickly jot down three top three systems changes in which they are interested. These systems changes may be ones that they would like to come faster, or ones they would like to not happen. \n \nStep 2: A two-dimensional map will be presented. Individuals will be asked to place their top three systems changes with axes along: \n– urgent to important; and \n– local to distant (Pepper, 1934; Tolman and Brunswik, 1935). \n \nStep 3: In groups, each individual will be asked to show their mappings, and provide background for having prioritized those interests. \n \nStep 4: Authentic systems thinking orders synthesis (putting thing together) before analysis (taking things apart). Each group will be encouraged to attempt to synthesize its priorities across its participants. \n \nStep 5: One reporter from each group will reflect on their collective experience on reordering priorities. \n \nArtifacts and comments from the group reports will be collected for summarization, possibly for publication in the proceedings. This knowledge-creating exercise will be used to refine methods for groups engaging in action learning. \n \nThe Systems Changes Learning Circle (founded 2019) is a group convening at the Centre for Social Innovation (Toronto) emerging from Systems Thinking Ontario (founded 2012). We include postgraduates and instructors from the Strategic Foresight and Innovation Program at OCADU in Toronto. Our content at licensed as Creative Commons at http://systemschanges.com . We cooperate with the Open Learning Commons at http://openlearning.cc , and the Digital Life Collective at http://diglife.com
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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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.051 | 0.017 |
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".