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Record W2164112819 · doi:10.5539/jsd.v6n11p43

Reviewing the Ambiguous: Examining the Typologies of Public Participation Towards Its Evaluation

2013· article· en· W2164112819 on OpenAlexvenueno aff
Ashiru Bello, Kamariah Dola, Yazid Muhammad Yunos, Ainul Jaria Maidin, Suhardi Maulan

Bibliographic record

VenueJournal of Sustainable Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsTypologyPerspective (graphical)Citizen journalismPublic participationSociologyParticipatory planningDual (grammatical number)Participatory evaluationPublic engagementManagement sciencePublic relationsPolitical scienceSocial scienceComputer scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Arguments surrounding the epistemology, as well as practical manifestation of various typologies of public participation are enormous. This highlights not only the fluid and complex nature of the concept but also how strongly tied it is to time and place. While the typology of public participation is often viewed from the perspective of engagement levels, this paper uses a dual perspective approach to discuss the various forms of participation from the perspective of both engagement levels and motives, to that of specific contextual applications. The paper also draws from the practical experiences of planners in Malaysia and Nigeria to examine the relationship between evaluation approaches for public participation and the successes of participatory processes in planning projects. The perceived contribution of participatory mechanisms to a project’s success is found to be inadequate in explaining the technique’s contribution to the overall success of planning projects. Also, the motivation of (ex-ante) evaluation is more a determinant of the project success than the focus of evaluation. There is therefore a need for coherent frameworks to integrate previous evaluation experiences in to subsequent policy guides to improve further evaluation efforts as well as planning projects.

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)0.015
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.275
GPT teacher head0.438
Teacher spread0.163 · 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.

Study designOther design
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

Citations1
Published2013
Admission routes1
Has abstractyes

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