Mysterious geographies : the scaped spaces of Eleanor Bond, Janet Cardiff and Brenda Pelkey
Bibliographic record
Abstract
This thesis explores how the works of Eleanor Bond, Brenda Pelkey and Janet Cardiff emphasize the inseparability of represented space from human perception, and the crucial role played by such physical and cultural concerns as the body, memories, stories and dreams in the shaping of spaces. Their works refer, therefore, not simply to physical spaces, but to conditions or states of space, often determined by layers of metaphorical significance which these artists bring to light. It is these ephemeral transformations and psychic interventions which irrevocably alter our environments that constitute the scape, a concept which captures this building up of a network of human responses to one's environment which in turn change the way it is perceived and lived. In their insistence upon the impact of the elusive and metaphorical, these works constitute a decided intervention in the tradition of Canadian landscape art while remaining firmly embedded in discussions of space, situation and environment. By subverting hegemonic modes of spatial representation, Bond, Pelkey and Cardiff construct their own visual assertions of what spaces were, can, or could be. The creation of scapes becomes part of a process for re-shaping both perceived and lived space, collapsing binaries such as self and other, public and private, nature and culture, and reality and fiction, in order to encompass the range of concrete and metaphorical attempts to shape the spaces we inhabit.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".