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Record W2088742417 · doi:10.5539/enrr.v4n4p37

When Rhetoric Meets Reality: Attitudinal Change and Coastal Zone Management in Ghana

2014· article· en· W2088742417 on OpenAlexvenueno aff
Elaine T. Lawson

Bibliographic record

VenueEnvironment and Natural Resources Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsResource (disambiguation)RhetoricNatural resourceOrder (exchange)Positive attitudePsychologyEnvironmental resource managementSocial psychologyPolitical scienceBusinessEnvironmental science

Abstract

fetched live from OpenAlex

The current poor state of coastal natural resources in Ghana has been attributed to pressures largely from anthropogenic sources, as well as to the negative attitudes of resource users. In order to facilitate attitudinal change educational programmes have focused on the linear model of behaviour, where an awareness of environmental problems is thought to lead to positive environmental behaviour. This paper presents the results of a study of the environmental attitudes of some coastal residents and the socio-economic milieu in which these attitudes are expressed. The results indicated that (1) majority of the respondents lacked access to basic infrastructure, (2) their main environmental concerns were linked to their desire for better living conditions, (3) they have generally positive environmental attitudes and (4) their positive environmental attitudes did not translate to good environmental behaviour because of factors mentioned in (1) and (2). The paper recommends the consideration of environmental and socio-economic concerns of resource users, which influence behavioural intentions during the policy-making processes.

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 score0.421
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.317
Teacher spread0.272 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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