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Record W2893697425 · doi:10.5539/jsd.v11n5p227

Fishing Settlement in Nothern Coast of Jakarta: From Intimidation to Recognition

2018· article· en· W2893697425 on OpenAlexvenueno aff
Muhammad Obie

Bibliographic record

VenueJournal of Sustainable Development · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsnot available
Fundersnot available
KeywordsIntimidationLivelihoodFishingSettlement (finance)Government (linguistics)GeographyDemocracyData collectionPolitical scienceSociologyBusinessSocial scienceLawArchaeologyPolitics

Abstract

fetched live from OpenAlex

Coastal area becomes a meeting place of various interests, both the interests of the government to protect and exploit it, as well as local communities for their livelihood survival. This research analyzed the livelihood bases of fishing settlement in north coast of Jakarta, from the time of intimidation, until its existence was recognized by the government. The research strategy used historical case study. Collected data were primary and secondary data. Primary data collection was through in-depth interview and observation. Researcher in this case used biographical methods. Data analysis used a qualitative approach performed simultaneously during data collection took place, and after completion of data collection within a certain period. The secondary data was obtained through literature studies. The results of research showed that livelihood bases of fishing settlement in north coast of Jakarta rely on marine products. Fishermen in this settlement have a deep connection with the sea, so all the economic activities of the people are related to the sea. Since it was first inhabited in the 1970s, the region often got government intimidation which forced fishermen to leave the area. However, due to the fierce resistance of the citizens, the intimidation was ultimately unsuccessful. The government finally acknowledged the existence of fishing settlement after entering the reform era. It results the democratic tap was open where dialogue and negotiation by fishermen figures intensified.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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