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Record W4414321489 · doi:10.15273/jue.v15i2.12531

Food as a Method of Placemaking for Latin American Immigrants in the US South: A Case Study of a Neighborhood in South Nashville, TN

2025· article· en· W4414321489 on OpenAlexvenueno aff
Justin Luckner

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsPlacemakingImmigrationLatin AmericansEthnographyParticipant observationIdentity (music)Food culture

Abstract

fetched live from OpenAlex

Diverse groups of immigrants from Latin American countries populate modern-day Nashville like many other urban areas in the US South. Since the 1990s, immigrants from Mexico and other Latin American countries have migrated in high numbers to the region, leading to the creation of terms like “Nuevo South.” In Nashville, Latinx immigrants have culturally expressed themselves through food and food institutions have acted as impetus for a sense of community. International grocery stores and cultural restaurants not only act as mediums to spread and establish a sense of culture, but also as places for communities to form and learn from one another while integrating into a new environment. This paper will examine existing literature on the recent influx of immigration to the US South and the expression of culture via food in immigrant neighborhoods. This paper will employ Karen O’Reilly’s 2012 definition of participant observation ethnographies and Mark Wyckoff’s 2014 definition of placemaking to analyze immigrant-owned restaurants and grocery stores along Nolensville Pike in South Nashville as places of community. This paper seeks to prove that these food institutions constitute vital methods of placemaking for immigrants in the US South.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.307
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.379
Teacher spread0.327 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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