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Record W7135991963

Reporting with purpose? Preliminary findings from a study of the first year of PRME SIP 2.0

2025· article· en· W7135991963 on OpenAlexaff
Petros Vourvachis, Laura Steele, Margaret McKee, Fara Azmat, José Luis Camarena, Jason Garcia Portilla, Ifigenia Georgiou, Alexandra Grammenou, Anna Hobenadel, Belen López Vázquez, Alejandro Luna, Frédérica Martin, Karen Neville, Katerina Psarikidou, Nahid Yazdani, Gustavo A. Yepes López

Bibliographic record

VenueZürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsConcordia UniversityConestoga CollegeQueen's University
Fundersnot available
KeywordsSustainabilityTransparency (behavior)Sustainability reportingStakeholderStakeholder engagementCorporate social responsibilityStakeholder management
DOInot available

Abstract

fetched live from OpenAlex

The Principles for Responsible Management Education (PRME) is a United Nations (UN) supported initiative established under the aegis of the UN Global Compact to raise the profile of sustainability in business and management education. PRME is underpinned by seven Principles that seek to guide business and management schools towards the holistic integration of ethics, social responsibility, and sustainability into their mission, vision, strategy, curricula, research, partnerships, and operations. Sharing Information on Progress (SIP) reporting is a key commitment for all PRME Signatories, as well as an important vehicle for engaging institutional stakeholders. In 2024, PRME introduced a revised reporting framework (‘SIP 2.0’), as well as a new reporting platform, the PRME Commons. The aim of these changes was to improve transparency and accountability, enhance learning, promote dialogue, capture impact, strengthen alignment with the Principles of PRME, and–not least–streamline the reporting process. This working paper presents the initial findings from a project analysing the content of over 160 SIP 2.0 reports submitted in 2024. It draws attention to the strengths of the new approach, highlights areas for development, and seeks to stimulate discussion on what makes for an ‘excellent’ SIP report according to different stakeholder perspectives.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.272
Teacher spread0.256 · 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
Published2025
Admission routes1
Has abstractyes

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Same venueZürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)Same topicSustainability in Higher EducationFrench-language works237,207