Bibliographic record
Abstract
Meaningful Stakeholder Engagement (MSE) is both a concept and a management approach, drawing on a combination of theoretical and applied knowledge areas (e.g., impact assessment, business and human rights, and stakeholder theory). MSE has become a key element of corporate sustainability risk-based due diligence as a process that responsible business enterprises are expected to apply to identify and manage harmful impacts on the environment and society. \n \n Despite the obvious and growing relevance of meaningful stakeholder engagement, few publications have tried to synthesize the knowledge, academic literature, and practical experience within and around the concept and practices. This volume responds to that knowledge gap through the provision of comprehensive interdisciplinary perspectives. Embodying a rights-holder orientation, The Routledge Handbook on Meaningful Stakeholder Engagement emphasizes the importance of MSE for stakeholders who are or can be affected by activities driven by external actors, such as natural resource extraction or processing; infrastructure; development proposals, planning and implementation; and production for industry or consumption. \n \n This handbook offers four thematic sections, all interdisciplinary in character, seeking to explore the multiple aspects of MSE. Moreover, a comprehensive introductory chapter explains key elements of the concept and causes for the current surge in expectations of MSE, including a rise in demands of risk-based due diligence. More than 40 international contributors combine theory and practice in chapters that discuss and elaborate the theory and practice of MSE. Uniquely, each section includes short practice notes based on experiences or dilemmas lived by practitioners or affected people, placing real-life situations into theoretical context. The concluding chapter draws up key insights from the chapters and practice notes, and casts a path for the future of MSE integrating values, norms, and practice. \n \n Cutting across multiple disciplines including stakeholder theory, natural resource management, impact assessment, project management, ESG, responsible business, and global value chains, The Routledge Handbook on Meaningful Stakeholder Engagement will be an essential resource for scholars, researchers, developers, investors, affected people, civil society organizations, students, and others. \n \n The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.816 | 0.990 |
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; both teacher heads agree on what is shown here.
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".