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US campus and university debit card policies regarding tobacco and electronic cigarettes

2014· letter· en· W2107470616 on OpenAlexaboutno aff
Lindsay N. Boyers, Chanté Karimkhani, Jennifer R. Riggs, Robert P. Dellavalle

Bibliographic record

VenueTobacco Control · 2014
Typeletter
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsDebit cardCashBusinessCredit cardUniversity campusAdvertisingQuarter (Canadian coin)PaymentFinanceLibrary scienceComputer science

Abstract

fetched live from OpenAlex

A modern advancement of university student identification cards is the ability to load the card with ‘campus cash’, converting it to a debit card that can be used to purchase goods and services at various university-affiliated merchants on-campus and off-campus. Students or, more commonly, parents can load these university debit cards with money. Policies regarding the use and management of these debit cards are institution specific. Some universities allow use of campus cash at off-campus vendors while others limit the debits cards for on-campus use only, such as dining halls and convenience stores. A prior study discovered that 42% of surveyed university students used their university debit card to purchase cigarettes.1 In addition, more than one-quarter million youth who had never smoked a cigarette used electronic cigarettes (e-cigarettes) in 2013.2 This exploratory investigation assessed campus and university-affiliated debit card policies regarding tobacco and e-cigarettes at major American universities. The university debit card policies regarding tobacco products and e-cigarettes at the top 100 universities according …

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0120.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2014
Admission routes1
Has abstractyes

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