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Record W3110452638

Dumping like a state: An environmental history of the City of Vancouver Landfill in Delta, 1958–1981

2020· dissertation· en· W3110452638 on OpenAlexaboutno aff
Hailey Venn

Bibliographic record

VenueSummit (Simon Fraser University) · 2020
Typedissertation
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsDumpingDeltaState (computer science)GeographyEnvironmental planningEnvironmental scienceEngineeringBusinessComputer scienceInternational trade
DOInot available

Abstract

fetched live from OpenAlex

In 1966, the City of Vancouver opened a new landfill in Burns Bog, in the nearby municipality of Delta.This is an environmental history of its creation and first sixteen years of operation.Although the landfill resembled other high modernist projects in postwar Canada, this thesis argues it is best understood as an example of "mundane modernism."The landfill's planning and operation aligned with broader contemporary American and Canadian practices of cost-effective waste disposal.It was an unspectacular project to which Deltans offered little initial resistance.Officials therefore had no need to demonstrate technoscientific expertise to manufacture citizens' consent.Yet the landfill soon posed environmental nuisances and hazards to Delta's residents, including leachate, the liquid waste a landfill produces.Although Deltans mounted some protests, the mutually beneficial relationship between the municipalities of Delta and Vancouver protected the landfill's operators from the consequences of mismanagement and allowed that mismanagement to continue throughout the 1960s and 1970s.This thesis suggests that further scholarly attention be paid to the history of solid waste management in Canada, and especially to specific sites such as the Burns Bog landfill.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.056
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0240.006
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.007
GPT teacher head0.169
Teacher spread0.162 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueSummit (Simon Fraser University)Same topicAmerican Environmental and Regional HistoryFrench-language works237,207