Rethinking the post-extraction landscape : an architectural inquiry into post-extraction conditions
Bibliographic record
Abstract
A common theme amongst all communities dependent upon the extraction of mineral resources is their dependence upon a finite mineral reserve. Once exhausted or abandoned due to a loss of economy in extraction or in favour of more promising and profitable prospects, communities are frequently left to contend with the residual impacts of mining. The effects of which have only been amplified in recent years due to changing modes of production and consumption. As a consequence of these conditions, former industrial sites, particularly those related to primary resource extraction, have fallen into disuse. Physically altered and transformed by extractive industry, these once active extraction sites now remain as dormant voids, artifacts of industry. In light of these conditions, this thesis advocates for the reclamation of postextraction landscapes using architecture as a tool for highlighting, preserving and repurposing the now dormant industrial void. Having evolved in relation to both natural and cultural conditions, architecture acts to inform and reconnect users with former extraction sites, while fostering a greater understanding and awareness of the intertwined nature of industry, landscape and the history of place as it is linked to former industry (Hough M. , 1990). Marmora, located in southern Ontario and one of the first iron mining communities in Upper Canada, is the context for this investigation. This community, like many others, flourished with the discovery of rich mineral deposits in the region early in the 19th century. Dependent upon a finite mineral reserve Marmora’s economy deteriorated with the collapse of industry in the region late in the 20th century. Despite this condition, this small community continues to thrive due to its strong agricultural, recreation and tourism sectors which continue to drive the community’s economy since the collapse of industry. What remains of the community’s fleeting industrial past however, is a now abandoned open pit mine, the place of intervention for this study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".