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Record W2087914770 · doi:10.1080/14634980600561466

A proposal for the application of integrated coastal management for institutional arrangements in Xiamen

2006· article· en· W2087914770 on OpenAlexaff
Liyu Zhang, Xiongzhi Xue, Qinhua Fang, Shawn Shen

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPreconditionEnvironmental resource managementCoastal managementResource (disambiguation)BusinessEnvironmental planningResource management (computing)Computer scienceGeographyEnvironmental science

Abstract

fetched live from OpenAlex

Integrated Coastal Management (ICM) is a feasible approach to address coastal issues, including resource use conflicts, ecological environments and management issues. An institutional arrangement is a precondition for the fulfillment of management functions. Therefore, a scientific institutional arrangement must be established as soon as possible for more effective implementation of ICM. In this paper, theories on ICM institutional arrangements were analyzed. In addition, characteristics and lessons learned domestically and internationally from the ICM institutional arrangements were summarized. Finally, based on the issues encountered in the first Xiamen ICM implementation, as well as on the major existing problems faced in Xiamen's coast, establishing a new ICM institutional arrangement for Xiamen was proposed.

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)0.007
metaresearch head score (Gemma)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0070.006
Open science0.0020.006
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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