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Record W2605230100 · doi:10.1080/0194262x.2017.1298493

Sustainability Engineering Collection Assessment: A Mixed-Method Analysis

2017· article· en· W2605230100 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

VenueScience & Technology Libraries · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsMcGill University
FundersMcGill University
KeywordsSustainabilityComputer scienceLibrary science

Abstract

fetched live from OpenAlex

Sustainability is a growing concept across many disciplines and has recently drawn attention from engineers. This study aims to assess the research materials used by faculty members in the Trottier Institute for Sustainability in Engineering and Design (TISED) at McGill University using a mixed-method approach of citation analysis and interviews. While citation analysis reveals important citations behaviors of TISED members and suggests top journals for engineering collections, interviews further identified faculty’s perceptions and expectations of the library’s collection and service. These findings can be useful for engineering librarians to develop the collections and services that are relevant to faculty’s research needs.

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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.008
Science and technology studies0.0070.007
Scholarly communication0.0010.003
Open science0.0020.000
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 head0.010
GPT teacher head0.377
Teacher spread0.367 · 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