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Record W2015566308 · doi:10.3152/146155109x479459

The contribution of capacities and context to EIA system performance and effectiveness in developing countries: towards a better understanding

2009· article· en· W2015566308 on OpenAlex
Arend Kolhoff, Hens Runhaar, Peter Driessen

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 · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsDeveloping countryContext (archaeology)Sustainable developmentConceptual frameworkEnvironmental planningBusinessEnvironmental resource managementPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

EIA has the potential to contribute towards more sustainable development through well-informed decision-making.Evaluation studies conclude that this potential is utilised to a considerable extent in rich western democratic countries such as Canada and The Netherlands, but hardly in developing countries.EIA capacity development programmes have not been able to structurally change this situation in developing countries, where there is lack of insight into the root causes of low EIA performance.There is growing evidence that context-specific characteristics such as the political system and the capacities of the key stakeholders are insufficiently considered in evaluations of EIA system performance.Most evaluations focus primarily on procedural shortcomings.As a consequence, capacity development activities that arise from EIA system evaluations do not tackle the underlying constraints.The aim of this article is to identify factors influencing EIA system performance in developing countries, and a conceptual model was developed to provide insight into those factors, building on a review of the current approaches and insights.A thorough assessment of EIA system performance is considered a necessary first step before capacity development activities can be identified, aiming to develop EIA systems that utilise the potential for EIA in a country.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.349
Teacher spread0.325 · 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