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Greening the campus without grass: using visual methods to understand and integrate student perspectives in campus landscape development and water sustainability planning

2011· article· en· W1520004203 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArea · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsDalhousie UniversitySimon Fraser University
FundersDalhousie University
KeywordsSustainabilitySustainable developmentLandscape planningValue (mathematics)Urban planningEnvironmental planningResource (disambiguation)Environmental resource managementSociologyGeographyPolitical scienceEngineeringCivil engineeringComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

Water, once thought to be a limitless resource, is now recognised as finite and one of the most contentious, uncertain issues of the future. While universities are one of the largest users of potable water in the urban landscape, they are also widely regarded as leading sources for innovative solutions and showcasing ways forward in environmental sustainability. However, universities are also sites of power where decisions are often made without democratic engagement with their major stakeholders: students. This paper is part of a larger study that examines how undergraduate students in geography (n = 98) perceive and value water conservation initiatives on an urban Canadian campus. The research involved administering a survey focused on identifying barriers to participation in sustainability initiatives and how involvement in sustainable activities on campus can alter the landscape. An important part of the survey, and the focus of this paper, was to examine how participants evaluated and ranked photographs of prospective campus landscape images and how they perceived its value. This method offers a way forward from how the traditional expert-based mapping and development of the campus landscape can effectively incorporate student values. Emphasis is placed on the desirability of student-based involvement in the evaluation and mapping of future land use development on the campus. Implications of communication barriers between students and policymakers are discussed with suggestions as to how student values, identified through the use of alternative landscape imagery, can be integrated into traditional landscape development and campus planning. Recommendations are made as to how community mapping, which enables communities to share information through a mapping structure, can be utilised to facilitate unique, inclusive and sustainable landscape planning, and to help integrate future student-directed sustainability projects.

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)0.001
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 score0.013
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.059
GPT teacher head0.363
Teacher spread0.304 · 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