MétaCan
Menu
Back to cohort
Record W7112163275

Seadoo Seaway: Four Tales of Cultural Imaginaries and Climate Futures on the Trent-Severn

2024· article· en· W7112163275 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Futures contractRecreationClimate changeThe ImaginaryNeoliberalism (international relations)
DOInot available

Abstract

fetched live from OpenAlex

Water, ice, and snow are key figures of Canadian cultural identity, and rightly so as Canada has more bodies of water than the rest of the world combined. This cohabitation with water has sponsored a unique cultural landscape, shaping ideas of leisure, sport, and recreation directly informed by water in all its states. The Seadoo Seaway looks to understand, augment, and expand this cultural landscape within the context of changing climates, and resultantly changing relationships between Canadians and water. The project investigates this change within the Trent-Severn Waterway, a recreational waterway in Southern Ontario that is at the forefront of both contemporary reproductions of this cultural imaginary, and rapidly changing climate as the region is set to be the first in the nation to experience winters without frozen waters. The goal of the project is not to longingly reproduce relationships with water but to accept climate realities and provide modes to expand this cultural imaginary into new relationships with water, in all its forms.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.077
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0360.026
Scholarly communication0.0100.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.031
GPT teacher head0.275
Teacher spread0.244 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDigital Access to Scholarship at Harvard (DASH) (Harvard University)Same topicWater Governance and InfrastructureFrench-language works237,207