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Record W3110279087 · doi:10.1075/ll.19005.pha

Memories and semiotic resources in place-making

2020· article· en· W3110279087 on OpenAlexaboutno aff
Nhan Phan

Bibliographic record

VenueLinguistic Landscape An international journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSemioticsMeaning (existential)Triad (sociology)SociologyContrast (vision)Value (mathematics)LinguisticsAffect (linguistics)Quarter (Canadian coin)Identity (music)Place makingSense of placeAestheticsHistoryEpistemologyCommunicationArtSocial scienceComputer sciencePhilosophyArchaeology

Abstract

fetched live from OpenAlex

Abstract This paper explores how semiotic resources are used to build individuals’ place-making during a walk around the Old Quarter in Hanoi, Vietnam. Using Lefebvre’s (1991) spatial triad as the perceived, the lived and the conceived, the paper uses a case study of a local participant and myself to consider how our differing perspectives affect place-making. I show how the local resident makes meaning using perceived resources in the here-and-now as backdrops for the lived, presented via his recounting of memories of activity spaces. I then contrast how these memories differ from the researcher’s place-making, where the conceived affects how I perceive the significance of visual resources on signs in the here-and-now. The study shows the value of Lefebvre’s (1991) triad for explaining the conflicting generalisations researchers have made about the nature of what is seen in the linguistic landscape or about the roles played by linguistic landscape in defining place.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.022
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.056
GPT teacher head0.440
Teacher spread0.384 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueLinguistic Landscape An international journalSame topicMultilingual Education and PolicyFrench-language works237,207