Recasting Jung Through an Indigenist Approach to Deepen Shared Knowledges of Well-being and Healing on Australian Soils: Protocol for a Qualitative Landscape Research Study
Bibliographic record
Abstract
BACKGROUND: The colonization of Australia is responsible for complex layers of trauma for the First Nations peoples of the continent. First Nations Australians' well-being is irrevocably tied to the well-being of the land. The application of a landscape-based approach to collaborative research shows promise in enabling genuine relationships that yield rich and informative data. However, there is a lack of practical evidence in the field of landscape research-research tied to First Nations Australians' worldviews of landscape. OBJECTIVE: This study aims to deepen shared knowledges of well-being and healing on Australian soils. We aim to examine ritual co-design as a novel method for deepening these shared knowledges. METHODS: This research comprises a qualitative and participatory action research design operationalized through an Indigenist approach. It is a 2-phase project that is co-designed with First Nations Australians. Phase 1 of this project is a relational study that endeavors to deepen the theory underpinning the project, alongside the development of meaningful and reciprocal community connections. Phase 2 is a series of 3 participatory action research cycles to co-design a new communal ritual. This process seeks to privilege First Nations Australians' voices and ways of knowing, which are themselves communal, ritual, and symbolic. The framework developed by psychiatrist Carl Jung informs the psychological nature of the enquiry. An Indigenist approach to landscape research recasts the Jungian frame to enable a culturally safe, context-specific, and landscape-based method of qualitative research. RESULTS: The research is in the preliminary stages of participant recruitment. It is expected that data collection will commence in late 2022. CONCLUSIONS: It is expected that this qualitative and co-designed project will strengthen the cross-cultural co-designer relationships and that the data gathered from these relationships, and the accompanying practical outcomes, will provide new insight into the interaction between human and landscape well-being. The field of landscape research is in an embryonic phase. This new field is embedded in the understanding that First Nations Australians' well-being is irrevocably tied to the well-being of the land, and this study seeks to build on this evidence base. A strength of this research is the relational methodology, in which First Nations Peoples' needs and desires will inform future research directions. It is limited by its context specific nature; however, it is expected that findings will be usable in guiding future research directions in the multidisciplinary field of landscape research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/36328.
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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 | 0.096 | 0.083 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.040 | 0.012 |
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".