Garden of resilience : individual, clinician, and Indigenous community stories of disruption and adaptation during the 21st century
Bibliographic record
Abstract
When individuals, communities, and societies experience stressors and occupational disruptions, they must draw upon their resilience to adapt to and cope with these events. However, resilience is not a homogenous topic but must be understood within specific disruptions and sociocultural contexts. This dissertation aims to explore and synthesize people’s experiences of occupation and resilience in two situations of occupational disruption in British Columbia (BC), Canada: 1) record-breaking wildfires in northern BC and 2) the first year of the COVID-19 pandemic. Study 1: A scoping review summarizing resilience research in occupational science and occupational therapy was conducted, highlighting important scholarly work to date and areas for further theoretical development (Chapter 2). Studies 2 and 3: A two-part qualitative research project investigating experiences of wildfires among Carrier and Sekani First Nations communities was undertaken. This project occurred in partnership with Carrier Sekani Family Services (CSFS)—a First Nations-led healthcare, social services, and research organization that serves First Nations people in north central BC. In part one, a thematic analysis of virtual interviews with 10 CSFS employees regarding the 2018 wildfire season identified stories of disruption and resilience (Chapter 3). In part two, critical perspectives were applied to analyze 14 interviews (mostly conducted in person) with people living and working in the First Nations communities served by CSFS regarding the 2018 and 2021 wildfire seasons, revealing the contradictory nature of wildfires as traumatic and destructive events that can—simultaneously—inspire communities to come together and cause needed reckonings with limitations in current resilience practices (Chapter 4). Study 4: A qualitative secondary analysis was conducted of interviews with stroke survivors regarding their experiences of occupation and resilience during the initial months of the COVID-19 pandemic in BC. This study showed how previously living through the life-changing event of a stroke prepared survivors to be resilient to the social and occupational impacts of the pandemic (Chapter 5). Together, these studies demonstrate the interconnectedness between resilience and occupation. Drawing upon his perspectives as a Métis occupational therapist and scholar, this dissertation’s author highlights some research, clinical and policy-related lessons stemming from the work (Chapter 6).
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.047 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".