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Record W7147461059 · doi:10.64126/jrs.v1i1.10

Pengembangan Taman Kota Sebagai Ruang Ketiga (Third Place) Di Kota Banda Aceh

2025· article· W7147461059 on OpenAlexaff
Syifaurrahmah Syifaurrahmah, Sylvia Agustina, Muhammad Yusuf

Bibliographic record

VenueJurnal Realitas Sosial · 2025
Typearticle
Language
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsRecreationPopulationField researchTourismFishingPublic park

Abstract

fetched live from OpenAlex

Rapid urban growth and population increases in Banda Aceh have heightened the need for public spaces that support community interaction. City parks have emerged as potential "third places," providing environments distinct from home and work. This study evaluates three parks in Banda Aceh — Blang Padang Field Park, Sari/Bustanussalatin Park, and Krueng Neng Park — against criteria such as openness, flexibility, and contextuality relevance. Using mixed methods, including field surveys, observations, and questionnaires distributed to 100 visitors, the research highlights these parks as inclusive social hubs. Each park has distinct roles: Blang Padang serves as a social and sports hub, Taman Sari emphasizes historical and cultural connections, and Krueng Neng prioritizes family-oriented facilities like playgrounds and fishing areas. Despite their benefits, issues like cleanliness, safety, and inadequate facilities need attention to enhance their utility. Recommendations include adding sports facilities and Wi-Fi to Blang Padang for students and freelancers, transforming Taman Sari into a cultural hub with art and discussion spaces, and enhancing Krueng Neng with better family recreation amenities and accessibility. With improved management, these parks could foster social bonds, offer dynamic interaction spaces, and elevate Banda Aceh residents’ quality of life.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.022
GPT teacher head0.264
Teacher spread0.242 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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