Dùthchas, a Scottish Gaelic Methodology to Guide Self-Decolonization and Conceptualize a Kincentric and Relational Approach to Community-Led Research
Bibliographic record
Abstract
A researcher’s worldview shapes the research methodology, design, and ensuing relationship with participants and the local environment. Western research has traditionally been carried out on, rather than in collaboration with Indigenous Peoples and has largely been conducted through eurocentric and ethnocentric knowledge systems, methods, values, and beliefs which have perpetuated extractions, racisms, and harm. To counteract harmful research, Indigenous scholarship stresses the necessity of articulating and clarifying researcher positionality and self-location prior to embarking on research with or by Indigenous communities. A fundamental component of positionality and self-location is clarifying one’s own relationships with colonialism and embarking on a process of self-decolonization. With this focus in mind, this paper shares methodological insights from an Anishinaabe community-led pilot project for Indigenous language revitalization in the Great Lakes Region of Turtle Island (also known as North and Central America) with participants to whom the researcher is related by marriage or known. This paper adds to existing qualitative methodological knowledge by introducing and operationalizing Dùthchas—a millennia-old Scottish Gaelic concept, worldview, and way of life—as kincentric methodology. The researcher begins the methodological inquiry with his own positionality and self-location as a Gàidheal (Scottish Gael) who is not Indigenous to Turtle Island. Following Dùthchas, the researcher identifies five key methodological principles that informed a kincentric and relational approach to community-led research. The paper demonstrates how Dùthchas has served as a guide for the researcher’s ongoing self-decolonization processes and for emplaced ethical relations. The paper illustrates how Dùthchas enabled the researcher to be in-relation to the lands and Peoples where the research project took place and to conceptualize and conduct research as part of a greater Indigenous Anishinaabe research paradigm, Mino-Bimaadiziwin (The Good Life). Dùthchas has implications for Indigenous—non-Indigenous reconciliatory relations and for the conceptualization and implementation of future (qualitative) research in-relation methodologies.
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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 | 0.028 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".