The Kingdom, the power, and the story. An analysis of three storytellers working with biblical narratives for change and reconciliation in dysfunctional Western churches
Bibliographic record
Abstract
The Kingdom, the power, and the story. An analysis of three storytellers working with biblical narratives for change and reconciliation in dysfunctional Western churches This dissertation considers storytelling as a vehicle for empowerment, change and reconciliation in three English-speaking, western Christian denominations: the Roman Catholic Church in Canada, a Church of England parish in Worcestershire, UK, and the UK Methodist Church. Considering the work of storytellers from these three contexts, the main argument is that storytelling empowers lay people to own their faith narratives and can be a vehicle for change and reconciliation. Furthermore, I ask can changing the story change the community? Following a brief historical background of the three denominations and the biblical texts that are used in the case studies, I consider the role of cognitive dissonance in the context of received beliefs. I consider the imbalance of power between clergy and laity with its potential to lead to abuse and dysfunctional Church communities and raise the issue of moving the process of storytelling in Churches closer to the realities of local communities as a solution to this dysfunction. I situate the storytelling in theatre and performance studies scholarship and explore insight from neuroscience and moral psychology scholars. The second chapter analyses the storytelling practice of Dr Megan McKenna on restorative justice in the context of the Canadian Truth and Reconciliation Commission. This is notable as little has been written from a theatre and performance perspective on the Roman Catholic Church’s response to the commission. The third chapter, set in a Church of England parish, examines my own practice, as an Anglican priest, bringing new approaches to the analysis of narrative transportation in storytelling in a faith context. The fourth chapter offers a new context to consider the theories of adaptation and alienation in storytelling through the practice of Ken Luxon in the UK Methodist Church, as a tool for the empowerment of lay people. In its examination of performative storytelling on the margins of established Church practice, this study provides new insight into the capacity for biblical storytelling to play a role in reshaping these Churches to provide solutions to their local dysfunction and to bring their local solutions to the dysfunction of the wider Church.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".