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Dari tekstual ke audiovisual: Transformasi La Galigo

2010· article· en· W26861752 on OpenAlexfundaboutno aff
Roger Tol

Bibliographic record

VenuePreventive Medicine · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsGeography

Abstract

fetched live from OpenAlex

Objective . Aboriginal people in Canada are at higher risk to heavy alcohol consumption than are other Canadians. The objective of this study was to examine a set of culturally specific correlates of heavy drinking among First Nations and Métis youth and adults. Methods . Demographic, geographic, socioeconomic and health-related variables were also considered. Data were used from Statistics Canada's 2012 Aboriginal Peoples Survey to predict heavy drinking among 14,410 First Nations and Métis 15years of age and older. Separate sets of binary sequential logistic regression models were estimated for youth and adults. Results . Among youth, those who had hunted, fished or trapped within the last year were more likely to be heavy drinkers. In addition, current smokers and those who most frequently participated in sports were at higher odds of heavy alcohol consumption. Among adults, respondents who had hunted, fished or trapped within the last year were more likely to drink heavily. On the other hand, those who had made traditional arts or crafts within the last year were less likely to drink heavily. Conclusions . Men, younger adults, smokers, those who were unmarried, those who had higher household incomes, and those who had higher ratings of self-perceived health were more likely to be heavy drinkers. Efforts aimed at reducing the prevalence of heavy drinking among this population may benefit from considering culturally specific factors, in addition to demographic variables and co-occurring health-risk behaviors.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.379
Teacher spread0.354 · 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 designNot applicable
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
Published2010
Admission routes2
Has abstractyes

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