Between Worlds: Artful Auto/Biography and/as Pagan Healing
Bibliographic record
Abstract
This dissertation draws upon the visual and oral life stories of thirteen participants (plus myself) to examine self-identified Pagan women and Pagan gender-variant persons’ experiences and memories of trauma and the potential healing power of storytelling. Specially, I use auto/biographical portraiture — framed as a form of self-guided visual life storytelling— to theorize links between embodied life experiences, traumatic experiences, and subjectivity. Geographically participants are located across Canada, United States, and Ireland where Paganism is still a minority religion, but also on the rise. Contemporary Paganism is a new religious movement that includes a plethora of religions and/or spiritual traditions located across diverse cultures and histories. Pagan religions are orthopraxical rather than orthodoxic; that is, it is shared practices that unite various Pagan religions rather than an official doctrine. However, contemporary Pagan epistemologies commonly encompass holistic paradigms, draw upon variously located vernacular religions and folk knowledges, and include belief in the supernatural beings and/or more-than-human worlds. Participants in this study locate their religiosity across the spectrum of Paganism.\nMy dissertation situates Pagan healing paradigms and practices within the scope of holistic healing and decolonizing trauma scholarship. In this context, auto/biographical portraiture is a form of creative and critical self-inquiry that can function as a medium for self-healing. My study finds that auto/biographical portraiture can be cathartic, empowering and healing, whether used alone or alongside other modalities of healing, including mainstream psychotherapy and/or Pagan healing rituals. For this reason, my findings can be useful for practitioners of conventional trauma discourse in supporting Pagans on their healing journeys. At the same time, this dissertation adds a feminist and decolonial trauma and violence-informed approach to Pagan practices.\nMy transdisciplinary approach places my research at the meeting place of arts-based, autoethnographic, feminist and decolonial methodologies and theoretical frameworks which make explicit that trauma and healing experiences are at once an interpersonal experience and a structural phenomenon. Thus, this dissertation makes clear that understanding Pagan persons’ experiences of trauma and healing necessitates an attentiveness to the structural roots of trauma, including gender and racial oppression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".