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Record W7135545758

Implementing PRME SIP 2.0: Insights from PRME Leads in the UK & Ireland

2024· other· en· W7135545758 on OpenAlexaff
Laura Steele, Petros Vourvachis

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsQueen's University
Fundersnot available
KeywordsSafeguardingTransparency (behavior)StakeholderSustainabilityBest practiceStakeholder managementKey (lock)
DOInot available

Abstract

fetched live from OpenAlex

The Principles for Responsible Management Education (PRME) is a United Nations-supported initiative that aims to raise the profile of sustainability in business and management education through Seven Principles focused on serving society and safeguarding our planet. One of the key commitments of PRME Signatory schools involves the submission of a Sharing Information on Progress (SIP) report. According to PRME, ‘the SIP's main objective is to serve as a public vehicle for information on responsible management education. In addition, the SIP can be an effective tool for facilitating stakeholder dialogue and a learning community among signatories’. Following extensive consultation and global pilot programme, in 2024 PRME introduced a new reporting framework for Signatories, colloquially known as ‘SIP 2.0’. Amongst other advantages, SIP 2.0 aims to enhance quality, consistency, and transparency in reporting. However, it also represents a significant–if generally welcome–change in approach for PRME leads and accreditation-related staff within business schools. In 2022, PRME Chapter UK & Ireland introduced biannual workshops on SIP reporting facilitated by Laura Steele. From 2023, these evolved to address SIP 2.0. In addition, as part of the 2024-2025 PRME Champions Cycle, Laura and Petros Vourvachis of Loughborough Business School are leading a project to analyse the new SIP reports and identify best practice. In June 2024, as part of the PRME Chapter UK & Ireland Conference at Exeter University Business School, Laura and Petros held a workshop exploring participants’ experiences in relation to SIP 2.0 to date. This article present a summary of the key points of discussion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.037
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0100.009
Scholarly communication0.0180.007
Open science0.0030.011
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0060.002

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 head0.035
GPT teacher head0.314
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

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