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Record W4395955547 · doi:10.18280/ijsdp.190406

Reviewing Algeria's Energy and Environmental Landscape: Policy, Regulation, and Knowledge Needs

2024· article· en· W4395955547 on OpenAlexvenueno aff
Belkacem Rabhi, Hanane Maria Regue, Toufik Benchatti, Ahmed Benchatti

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental planningEnergy (signal processing)Environmental resource managementEnvironmental policyBusinessNatural resource economicsPolitical scienceEnvironmental ethicsGeographyEnvironmental scienceEconomics

Abstract

fetched live from OpenAlex

Algeria faces a complex energy challenge: balancing rising domestic consumption with declining fossil fuel production and environmental concerns.Despite government efforts toward energy security and sustainability, progress has been slow.This review analyzes scholarly literature and existing regulations to identify knowledge gaps hindering a sustainable energy transition.The review identified existing policies targeting energy security and environmental sustainability.However, critical knowledge gaps remain in four key areas, The effectiveness of current policies for diversification, energy efficiency, and emission reduction needs further investigation.Research is needed on the effectiveness of existing regulations and the impact of potential subsidy reforms.Formulating regulations for a sustainable transport sector and addressing infrastructure challenges in unplanned urban areas are essential.Investigating domestic renewable energy manufacturing industries and grid integration of surplus renewable energy holds promise.Addressing these knowledge gaps is crucial for developing evidence-based solutions promoting a secure and sustainable energy future for Algeria.

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 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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2024
Admission routes1
Has abstractyes

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