MétaCan
Menu
Back to cohort
Record W2124213228 · doi:10.3152/147154605781765580

Learning from experience: emerging trends in environmental impact assessment follow-up

2005· article· en· W2124213228 on OpenAlex
Angus Morrison‐Saunders, Jos Arts

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental impact assessmentEnvironmental planningImpact assessmentEnvironmental resource managementEnvironmental sciencePolitical science

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.022
GPT teacher head0.397
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it