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Record W7043742435

Uncovering industrial symbiosis: a case study of Guelph, Ontario

2010· dissertation· en· W7043742435 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2010
Typedissertation
Languageen
FieldEngineering
TopicSustainable Industrial Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsInterpersonal tiesQualitative analysisQuantitative analysis (chemistry)Qualitative propertyIndustrial relationsWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis is an investigation of evidence of self-organized industrial symbiosis in a city. A case study of Guelph in Ontario, Canada was used to identify characteristics of inter-firm exchange of by-products, wastewater, and energy in a city with a diverse industrial base. Quantitative and qualitative data was collected from 22 firms in Guelph using an in-person interview method. The conditions that motivated these synergies and the nature of the relationship between firms were analyzed to provide an indication of the likelihood of further exchanges. 70 by-product synergies were identified. These exchanges predominantly involved arms-length transactions based on market mechanisms. They also were largely exchanged with recycling firms located outside of Guelph, but within a 100 km radius of the City. Stronger regulations and social ties may support more innovative exchanges and the growth of a regional industrial network.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.217
Teacher spread0.196 · 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 teacher head, not a consensus.

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
Published2010
Admission routes1
Has abstractyes

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