How to Mediate Around the World: Grassroots Examples of Peace, Prosperity and Happiness
Bibliographic record
Abstract
Book Description How to Mediate: Mediation for Peace, Prosperity and Happiness By David Hoicka, one of the Principal Mediators in Neutral Singapore Turn Conflict Into Dialogue: Your Practical Guide to Mediation Conflicts surround us—in families, workplaces, neighborhoods, and nations. Most of us feel helpless in the face of these divisions. But what if you already possess the skills to help? This groundbreaking book reveals that mediation isn't reserved for professionals. It's a human capacity we all share. Author David Hoicka, drawing on years of experience mediating, demonstrates how mediation has resolved conflicts conflicts worldwide. He shows you how to: · Create safety when tensions run high · Listen deeply to uncover what people truly need · Navigate emotions without being overwhelmed · Build agreements that actually last · Work with trauma and post-conflict situations · Help people coexist even when they can't reconcile Through compelling stories from Rwanda to Colombia, Northern Ireland to Indonesia, you'll discover mediation in action across cultures and contexts. Each chapter includes practice scenarios so you can develop your skills immediately. Whether you're dealing with a family dispute, workplace tension, community conflict, or simply want to engage with division more skillfully—this book provides the tools, wisdom, and encouragement you need. Conflict may be inevitable. Violence is not. Learn how mediation can bring peace, prosperity and happiness, and make a difference in your life, and lives around you. Perfect for: community leaders, professionals and workplace, educators, social workers, faith leaders, parents, and anyone looking to build better communities. Author Info: David Hoicka David Hoicka's goal is to help bring peace, happiness and economic growth to you, whether a person, group, company or homeland, through Mediation. If my books help save even one life, I will feel great happiness. David Hoicka is an award-winning mediator, and conducts mediations in neutral Singapore and elsewhere electronically and in person. He is one of the Principal Mediators, Mediation Coach and Mediation Assessor with Singapore Mediation Centre, and works with Singapore Mediation Solutions. He has conducted many hundreds of mediations. David Hoicka attended MIT, Suffolk Law School, Boston University School of Theology, and Upper Canada College. He lives in Singapore with his family Feel free to contact me through https://SingaporeMediationSolutions.org/contact/, or LinkedIn at https://www.linkedin.com/in/davidhoicka/
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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 | 0.002 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".