The Capacity of Shared Stories to Function as Myth and Encourage Inclusive Participation
Bibliographic record
Abstract
Beginning with a description of the way the myths of incarnation and trinity function to encourage collaborative social participation in the experience of the Morecambe Bay Poverty Truth Commission (http://www.morecambebaypovertytruthcommission.org.uk/), the paper will attempt to show that shared stories operate as myths that transform corporate behaviour. In Timothy Stacey’s words they "help people expand their imagination, overcome the instrumental lens through which they perceive their own lives, and revivify the spirit of political participation." The paper will draw in particular on Stacey, Saving Liberalism from Itself: The Spirit of Political Participation (Bristol: Bristol University Press, 2022); Julie Tomlin “The Spiralling Dance of Wisdom” in The Kenarchy Journal 1.3, 2020 (https://kenarchy.org/wp-content/uploads/2020/05/Kenarchy_Volume1.3.pdf) and Sue Mitchell and Francisco Jose Eiroa-Orosa, “Love your enemy? An aesthetic discourse analysis of self-transcendence in values-motivated altruism” in Roger Haydon Mitchell, ed. Cultivating New Post–Secular Political Space (London and New York: Routledge, 2019). Stacey’s applied research findings from his years researching among participants in the Metro Vancouver Alliance (https://www.metvanalliance.org.), Tomlin’s work on the instatement of feminine myths and Sue Mitchell’s iteration of the skills of dialogic listening are harnessed to substantiate the proposal that a greater recognition of the role of myth in contemporary society will encourage and facilitate genuine participation. The capacity of shared stories to offset the Western liberal tendency to see knowledge as a rational mathēsis by means of which experts induct the individual into a more or less passive role will be indicated. In conclusion some of the practical outcomes of Round One of the Morecambe Bay Poverty Truth Commission will be outlined in evidence of the socially transformative potential of shared story telling.
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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 | 0.049 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.021 | 0.091 |
| Scholarly communication | 0.029 | 0.042 |
| Open science | 0.005 | 0.047 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".