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Record W3193117824 · doi:10.15273/jue.v11i2.11041

The Social Functions of College Drinking: Pregaming, Priming, and Protecting the Liminoid Experience

2021· article· en· W3193117824 on OpenAlexvenueno aff
Céline Schreiber

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
Fundersnot available
KeywordsMilestoneSocial psychologyIdentity (music)PsychologyPriming (agriculture)Social identity theoryState (computer science)Public relationsSocial groupPolitical science

Abstract

fetched live from OpenAlex

The Harvard School of Public Health College Alcohol Study has concluded that, on average, one in three college students abuses alcohol regularly. However, while highlighting potential risks, academic literature largely neglects the social functions students derive from consuming alcohol. College represents an important milestone in an individual’s life and is characterized by what Turner (1969) called liminoid experiences, which involve a temporary suspension of social status, at bars, clubs, concerts, festivals, and college parties, often closely connected to alcohol consumption. This paper explores how women students’ practice of “pregaming,” that is, drinking alcohol in smaller groups before attending a social event such as a party, enables individuals to achieve the liminoid state while also providing opportunities to resist potential negative consequences of intoxication. College women use pregaming to build a support network with close friends, enabling them to ensure their physical safety. Beyond the integrity of their bodies, women also ensure that their actions during the liminoid experience of a college party are consistent with ideas they have of their personal identity. Although they temporarily suspend their social and personal identities during college parties, women prevent unwanted permanent changes of their sense of self by holding each other accountable to rules they establish during the pregame.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.362
Teacher spread0.290 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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