An archive of settler belonging: Local feeling, land, and the forest resource on Vancouver Island
Bibliographic record
Abstract
This dissertation explores the local, material, and affective processes of Settler (non-Indigenous) attachment to land on southern Vancouver Island, British Columbia. I describe these feelings for land as Settler belonging and my research is guided by a reflexive and interdisciplinary approach that seeks to “explain Settlers to ourselves.” Through original archival research and personal reflection, I argue that “(dis)possession,” a term that encompasses Settler efforts to take the land and belong to the land, is a generational process, one that is worked at over time in an effort to link the past with the present and serve future Settler belonging. Through a study of plants, forest resource extraction, roads and railways, park creation, and real estate development in the Cowichan Valley and Sooke-Juan de Fuca regions, I argue that Settler feelings for land manifest in locally specific and contradictory ways. I build upon studies of Settler colonialism and political economy in Canada by adapting the staples approach, as developed by Harold A. Innis, Mel Watkins, and others, to trace the intersection of belonging with the resource economy and the characteristics of Settler colonialism. This dissertation links historical and ongoing transformations in the relations of production, such as the conversion of private forestry lands into real estate, to reveal the ways in which belonging adjusts to political and economic changes that both assist and threaten its future. I argue that studying the locality of belonging contributes insight and nuance to our understanding of materiality and affect, class relations, the staple economy, and Settler colonialism’s broader processes. In doing so, I demonstrate that Settler attachment to land is entrenched and expanded through a series of recurring events that are shared, personal, and conflictual.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".