The Hydrogeography of Mourning: Mapping the Life and Loss of Alberta Wetlands
Bibliographic record
Abstract
In Alberta, 60-70 percent of wetlands have disappeared (Alberta Government, 2013, September 1). While this figure is used to quantify wetland loss in the province, it does not reflect the experiences of those emotionally impacted by such loss. Using Davidson and Milligan’s concept of emotional geography (2004) this thesis will explore grief in relation to wetlands within Alberta’s North Saskatchewan Watershed through the accounts and observations of some who inhabit the watershed and have been impacted by its transformation. Mapping the life and loss of wetlands is not a matter of locating geographical markers, rather it uses grief as a point of departure by making present the material, sensory, and emotional entanglements with wetlands, which then open to deeper research and analysis about wetland loss as part of Alberta’s settler history and ongoing economic development. For many who grew up on the Prairies, or who have spent a considerable amount of time with wetlands, grief is not only a response to their material loss, but rather a response to a disruption of one’s sense of being and place. Through the use of landscape ethnography and phenomenology as both a methodological and theoretical approach I examine the ways in which wetlands are not just backdrops to past experiences, but become part of living memory shaped in relation to kinship, home, and cultural politics. The North Saskatchewan Watershed is therefore a conceptual frame for imagining an emotional hydrogeography, one where wetland loss exposes a certain vulnerability in Being-with-wetlands, and in Being-without them.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".