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Record W2005805455 · doi:10.3152/147154606781765264

Towards a national strategic environmental assessment system in Lebanon

2006· article· en· W2005805455 on OpenAlexaff
Alissar Chaker, K. El-Fadl, Lamia Chamas, Maya Abi Zeid Daou, Berj Hatjian

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsStrategic environmental assessmentChristian ministrySustainabilityMainstreamEnvironmental planningGovernment (linguistics)Context (archaeology)Sustainable developmentEnvironmental systemsEnvironmental resource managementPolitical scienceEnvironmental impact assessmentMiddle EastStrategic planningBusinessGeographyEnvironmental science

Abstract

fetched live from OpenAlex

In an effort to mainstream environmental sustainability in the national development agenda, the Government of Lebanon is among the pioneers in the Middle East to launch the development of a national strategic environmental assessment (SEA) system that caters to the particularities of the Lebanese planning, regulatory and institutional context. This paper provides a critical overview of the approach followed by the Ministry of Environment for the development of an SEA system and its regulation. It also makes recommendations for facilitating SEA implementation and presents some of the early outcomes resultingfrom awareness raising during consultation on the development of the proposed system

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0050.002
Scholarly communication0.0120.006
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.368
Teacher spread0.345 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2006
Admission routes1
Has abstractyes

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