D5.1 Stakeholders Engagement with GDEI perspective Toolkit
Bibliographic record
Abstract
The IN-HABIT Toolkit aims to provide a set of guidelines, methods and tools for the wider engagement of stakeholders in the People-public-private partnerships (PPPPs). It includes instructions for stakeholders mapping and local needs assessment, selection criteria, structure, working rules and diversity management procedures, co-design methodology, and the necessary guidelines and templates for the creation and management of the four local IN-HUBs. The Toolkit is the basis for the training process of the Local Community Activators and provides the reference set for the management of the four local IN-HUBS established in the cities of Córdoba, Lucca, Nitra, and Riga. It supports the accomplishment of a fully inclusive process of co-creation, co-design, co-management, and co-monitoring of the innovative solutions envisioned by the four local PPPPs, with specific attention at the engagement of less represented and more at risk of exclusion stakeholders. The toolkit includes the Glossary, providing definitions of the main terms adopted by the project as agreed among the partners, the Gender, Diversity, Equity, and Inclusion (GDEI) guidelines, aimed at supporting the wider, just and equal participation of all social groups to the process, and the IN-HUBs Management guidelines, which provide tools and templates for setting the local PPPPs coordination structure, co-monitoring procedures, and to support the co-creation of innovative solutions with citizens and stakeholders. This Toolkit is a living set of guidelines, methods and tools, and it will be adapted throughout the entire process based on the needs coming from the contextual application to the issues of the territories and the feedback of the local communities using it. Its purpose is to provide a set of flexible instruments to support the development of solutions tailored to the peculiarities of the local communities and to support their transferability to other territories. The toolkit is created through a collaborative process steered by WP5 Lead Partner TSR in which the partners share methods and approaches to define a specific IN-HABIT methodology. Each time the document is updated all partners will be duly informed about it. The present version is the first collection of tools deriving from the training process of the Local Community Activators and will be improved and adapted through the actual development of the project activities on the territory. Once the guidelines and tools are consolidated through contextual application in the IN-HUBS, the toolkit will be condensed in visual synthetic form for dissemination purposes.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.029 |
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".