Learning from experience: emerging trends in environmental impact assessment follow-up
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Notice bibliographique
Résumé
HE HISTORY OF environmental impact assessment (EIA) follow-up is nearly as long as the practice of EIA itself. A large body of work produced in the 1980s was devoted to the topic and this set the scene concerning aims, approaches and techniques for EIA follow-up. A recent upsurge of interest in EIA follow-up has seen it become the topic for a series of workshops at the International Association for Impact Assessment (IAIA) conferences from 1999 to 2005. Many of the findings, deliberations and case studies presented at these workshops and elsewhere have been published in journal articles in recent years. Towards the end of last year we edited a book devoted to EIA and strategic environmental assessment (SEA) follow-up practice, drawing on experiences from around the world (Morrison-Saunders and Arts, 2004). A review of this book by Dr Alan Bond (University of East Anglia) is included in the Book Reviews section of this volume. Having produced this book, we did not think that there was much more to say on the topic. However, a series of papers presented at the 2003 and 2004 IAIA conferences demonstrated an emerging interest and expertise in follow-up in socio-economic matters in particular, as well as further innovations in follow-up of ‘traditional’ project biophysical impacts to include cumulative and health impacts and fledgling conceptualisations of what SEA follow-up might entail. This kindled our interest in editing a special edition of Impact Assessment and Project Appraisal (IAPA) devoted to follow-up, which would explore the latest developments in the field. The world-wide practice of EIA and follow-up is reflected in this special issue, which includes practitioner contributions from Australia, Brazil, Canada, Finland, The Netherlands, Portugal, South Africa and the United Kingdom. The articles in this volume are presented in a sequence that approximately mirrors the evolution of thinking and expertise in the field. In introducing the articles, we summarise some of the key lessons learned from the collective body of wisdom presented and offer some perspectives on future new directions for EIA follow-up, including the notion of follow-up for sustainability assurance. Firstly, though, it is appropriate to take stock of the current state of play and this is the purpose of the first article in the volume.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 découle