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Record W4382314599 · doi:10.24843/jrs.2023.v10.i01.p01

Sense of Place in the Commercial Area of Jalan Senopati, Kebayoran Baru Jakarta Selatan based on Community Perception

2023· article· en· W4382314599 on OpenAlexaff
Nikita Elizabeth Cristine, Elsa Martini, Dayu Ariesta Kirana Sari, Darmawan Listya Cahya

Bibliographic record

VenueRUANG-SPACE Jurnal Lingkungan Binaan (Space Journal of the Built Environment) · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsSense of placeSense of communityNeighbourhood (mathematics)PerceptionBaruContext (archaeology)SociologyGeographyAdvertisingPedestrianLikert scaleMedia studiesPublic relationsPsychologyPolitical scienceSocial scienceBusinessArchaeology

Abstract

fetched live from OpenAlex

A sense of place represents an individual's perception of belonging to a place, both emotionally and socially.A commercial area such as Senopati Street of Kebayoran Baru in South Jakarta has its own character and vibe.It is known as the most popular commercial neighborhood that has been well-visited by surrounding communities of Jakarta and far beyond.This study aims to identify the public's perspectives regarding the sense of place they feel when they visit Senopati streets.It implements a qualitative descriptive method aided by using a Likert scale computation.Study results reveal that the social and physical natures of Senopati Street have their own uniqueness, composed by the nature of its physical structures/buildings, environments, and social interactions amongst members of the surrounding communities.This research will be a reference to other studies that take commercial areas as case studies and discusses a sense of place in an urban context as their research focus.The latter is one of many pivotal issues in the study of urban planning and development.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.230
Teacher spread0.190 · 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 designQualitative
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

Citations3
Published2023
Admission routes1
Has abstractyes

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