Implementing PRME SIP 2.0: Insights from PRME Leads in the UK & Ireland
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".