Identification and application of the components of meaningful public participation in forest management
Notice bibliographique
Résumé
Public participation is a central principal of sustainable forest riranagement and is increasingly seen as an important method for facilitating fair and effective decisionmaking in forest management.Public participation is rapidly moving from a policy goal to a legal requirement in forest nuriagement in Canada.However, achieving meaningful participation continues to be a challenge.There is a growing body of research that is attempting to uncover and define what elements make public participation processes effective.This study builds upon this research by examining what makes a particþation process meaningful and investigating the potential for implementing more meaningful public participation in forest management.To achieve this, the specific objectives of this study are: 1) to establish the key components of meaningful public participation;2) to investigate current appro.aches to public participation in forest management planning; 3) to corsider levels of satisfaction with current participatory approaches within Manitoba's Mountain Forest Region by examining current practice in light of the components of meaningful public participation; and 4) to develop recommendations for public participation in forest management.A qualitative research approach was used to address the goals of the research including, structured standardized expert interviews, semi-structured participant interviews, and a review of the relevant literature.Structured standardized interviews were conducted with academics, practitioners, and professionals involved in the public participation field-The rezults of these interviews were used to develop the key i Abstract components of meaningful public participation These components were vetted and built upon during the second phase of interviews involving participants from four public participation initiatives in Manitoba's Mountain Forest Region.The results established a definition of meaningful public participation and several components of meaningful public participation.The components of meaningful public particþation identified by this research include, fair notice and time, integrity and accountability, fair and open dialogue, multiple and appropriate methods, learning and informed participation, adequate anl accessible information, participant motivatior¡ inclusiveness and adequate representation, and influence.The components of meaningftl public particþation outlined in this study provide insight into how to run a more meaningful public participation process and show promise for use as a straightforward guideline for developing and implementing public participation processes that are more meaningful.First and foremost, I would like to thank all of the interviewees for sharing their knowledge and experiences with me.I would also like to extend my gratitude to Louisiana Pacific, Manitoba Conservation, and Parks Canada for allowing me to study their participation processes.Secondly, I extend thanks to the members of my academic committee, all of whom have been a valuable source of guidance, support, and advice throughout the research process.Dr. A. John Sinclair
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,031 | 0,071 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,006 | 0,011 |
| Communication savante | 0,010 | 0,006 |
| Science ouverte | 0,002 | 0,009 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».