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Record W7008890619

Conflicting Identities of Garrison Creek

2018· other· en· W7008890619 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Element (criminal law)PoliticsUrban planningValue (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Toronto’s Garrison Creek has gained a near mythical quality in both the minds and the plans of the city’s people. In the century since its burial and integration into the combined sewer network, there has been a growing tension between the creek’s identity as an ecological entity, and its identity as a sewer. This research explores these two faces of the Garrison, the creek and the sewer in turn, and explores how different groups have come to relate to the creek in various ways. Due to these two identities, Garrison Creek exemplifies a false division in how we have come to value urban water by celebrating water on the landscape and simultaneously dismissing the water that flows through our pipes. Garrison Creek reminds us that these systems are the same. This division limits our ability to think comprehensively about urban water and recognize the complexity of these systems that we interact with daily. In the past 20 years, several plans and projects have made the creek a key element and have attempted to “bring it back” in ways both physical and symbolic. Through a critical exploration of these plans and projects through the lens of urban political ecology, this research attempts to gain a deeper understanding of the complexity of our relationship these urban watersheds. This research provides a fine-grain exploration of the city’s relationship to its buried water and the evolution of these relationships over time. While based in the history of this place, this research also attempts to look forward to understand how our relationship to urban water can be improved in the face of both increased urban flooding and a need for reconciliation in Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.491

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0440.030
Scholarly communication0.0130.004
Open science0.0020.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.001

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.

Opus teacher head0.012
GPT teacher head0.187
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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