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Record W4206040125 · doi:10.32920/ryerson.14663532.v1

An investigation of corporate responsibility & sustainability goals in the Canadian commercial real estate and construction sector

2021· preprint· en· W4206040125 on OpenAlexaffabout
Irena Stankovic

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsSustainabilityReal estateBusinessOrder (exchange)Resource (disambiguation)Environmental economicsCorporate social responsibilityQualitative researchAccountingFinanceEconomicsPublic relationsPolitical scienceEcology

Abstract

fetched live from OpenAlex

This thesis investigates the potential integration of leading Corporate Responsibility and Sustainability (CR&S) goals across selected Commercial Real Estate (CRE) firms, key anchor tenants, and construction companies within the Canadian market as they relate to office building assets. Current literature provides limited observations and analysis on CR&S within the CRE sector, particularly for the Canadian market. In order to address this gap and advance the principles of CR&S across the Canadian CRE sector, the research provides a comprehensive qualitative content analysis of publically available CR&S reports, along with interviews conducted with subject matter experts in the sector. Reduction of energy, water and waste consumption, along with associated GHG emissions have been identified as leading elements driving environmental resource management, which in turn is identified as the founding base for integrating CR&S goals across the Canadian CRE market. In addition to uncovering leading CR&S goals, the study identified market differentiators and regulatory compliance as key CR&S motivators, along with leading tracking and implementation measures for CR&S goals, and their associated internal and external barriers to integrating CR&S goals. Ultimately, the study provides an academic contribution in identifying environmental resource management as a base for CR&S integration across the Canadian CRE sector.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.277
Teacher spread0.243 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes2
Has abstractyes

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