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Record W4232920169 · doi:10.31979/etd.tqrf-gyt5

Planet Building

2010· dissertation· en· W4232920169 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSustainable Design and Development
Canadian institutionsYork University
Fundersnot available
KeywordsSustainabilityMultinational corporationBusinessValue (mathematics)Value creationSustainable ValueEngineeringManagementIndustrial organizationEconomicsComputer science

Abstract

fetched live from OpenAlex

With the increasing complexities of a globalized 21st-century world, the growing power of industry clusters makes corporations important actors in designing sustainable development strategies. This thesis presents an applied case study at CB Richard Ellis (CBRE) as the company designed and launched its award-winning Sensible Sustainability platform. The research was conducted to determine how a large multinational company could create a business case for sustainability, and the results illustrate that value exists for firms engaged in sustainability initiatives. CBRE's initial no-cost and low-cost activities resulted in increased operational efficiencies and lower costs. Over the course of the research period, the company migrated toward its more strategic Planet Building strategy and has begun to merge its financials with an environmental and a growing social agenda that supports the Triple Bottom Line of transformative sustainability. As a result, the company is engaged with more diverse stakeholders in new markets and is realizing the benefits of increased brand reputation, improved relationships with more demanding clients, and increased market share and revenue

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.563
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.202
Teacher spread0.199 · 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

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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