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Record W1973026095 · doi:10.2495/sdp-v6-n3-286-298

Process efficiency and outcome effectiveness in the united kingdom’s local air quality management regime

2011· article· en· W1973026095 on OpenAlexvenueno aff
James Longhurst, Oluwaseun Olowoporoku, Jo Barnes, Tim Chatterton, Enda Hayes, J.G. Irwin

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Air Quality Management
Canadian institutionsnot available
Fundersnot available
KeywordsDeclarationAir quality indexQuality (philosophy)Process (computing)Outcome (game theory)Local governmentGovernment (linguistics)Set (abstract data type)PoliticsBusinessEnvironmental planningProcess managementEnvironmental economicsEnvironmental resource managementOperations managementPublic administrationPolitical scienceComputer scienceEngineeringEconomicsEnvironmental scienceLawGeography

Abstract

fetched live from OpenAlex

The UK's Local Air Quality Management (LAQM) commences with a Review and Assessment which may lead to the declaration of an Air Quality Management Area (AQMA) where an exceedence of the Air Quality Objectives is confi rmed. A declaration initiates the development of Air Quality Action Plan (AQAP) intended to provide solutions to the identifi ed problems. There is no doubt that the LAQM framework has delivered a clear picture of elevated air pollution at specifi c locations in the UK, defi ned in temporal and spatial scales. However, the evidence to date suggests that delivering solutions to air quality problems is much more problematic, and has not been achieved at the rate expected when the framework was introduced in 1997. Despite the national policy intention and direction provided through the framework, the probability of achieving the traffi c-related Air Quality Objectives by the set dates in the UK Regulations is uncertain. Using evidence from several studies undertaken by the authors, this paper considers the implication of distinct policy disconnects which are present in the LAQM process. The key conclusion implies transition from procedural compliance with the diagnostic process of LAQM towards a more holistic approach that will require new means of internal communication and co-operation and external consultation at the local and central government level and the ability to confront political and economic vested interest.

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)0.002
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 score0.013
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.044
GPT teacher head0.302
Teacher spread0.259 · 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 designObservational
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
Published2011
Admission routes1
Has abstractyes

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