MétaCan
Menu
Back to cohort
Record W3121066493 · doi:10.22215/etd/2017-11968

Mining for Thetford's Identity: Reclaiming the Mine Sites of a Former Asbestos Town

2017· dissertation· en· W3121066493 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicLandscape and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAsbestosIdentity (music)Environmental planningArchitectureCivil engineeringArchaeologyEngineeringGeography

Abstract

fetched live from OpenAlex

Canada has a long history of production, use, and export of asbestos, starting in 1876 when the first Canadian asbestos mine opened.With the industrial era of asbestos nearing its end, postproduction asbestos towns will remain not only as urban entities but also -and perhaps more importantly -as communities.This thesis considers the question of a new architectural and landscape design strategy for Thetford Mines, a former asbestos town wavering between success and failure.At one time the driver of the city's economy and core of its identity, Thetford's asbestos mines are now an uncomfortable impediment to a holistic approach to urban development.This thesis addresses two main critical issues: 1) how to repurpose a former mine site?; and 2) how to reconcile a contested past with the town's presentday identity?The goal is to trigger both reconciliation with a problematic past as well as urban development for the present.This thesis would not have been possible without a number of important people.First, I owe my deepest gratitude to my advisor, Professor Janine Debanné, for her invaluable contribution to this thesis.Her presence throughout this year-long process was greatly beneficial and, more importantly, highly pleasant and appreciated.I also want to thank my thesis comrades, Michael Stock and Hannah Munroe, who have experienced along my side this rewarding, yet overwhelming, achievement.

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)0.003
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 score0.265
Threshold uncertainty score0.533

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0400.013
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.078
GPT teacher head0.299
Teacher spread0.221 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicLandscape and Cultural StudiesFrench-language works237,207