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Record W6969021074 · doi:10.5683/sp3/jyuo8e

The AGRI National Project: Online Panel Study [Canada]

2022· dataset· en· W6969021074 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBorealis · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of AlbertaUniversity of CalgaryUniversity of Lethbridge
Fundersnot available
KeywordsSample (material)HarmPanel dataLongitudinal studyData collectionComputer-assisted web interviewing

Abstract

fetched live from OpenAlex

<p>The AGRI National Project (ANP) was a three-year longitudinal study conducted by a multi-institute research team based at the Alberta Gambling Research Institute (AGRI). The aim of the study was to capture a national-wide picture of gambling and problem gambling in Canada. The ANP had ten research objectives. The Online Panel Study was one of three parts of the ANP and was central to many of the ten objectives. The aims of the study included but was not limited to:</p> <ul> <li>Determine provincial and demographic differences in gambling and problem gambling;</li> <li>Determine the prevalence of online gambling; and</li> <li>Determine the use of and perceived effectiveness of harm minimization initiatives in preventing problem gambling.</li> </ul> <p>The Online Panel Study collected data on several gambling-specific aspects of the responders' lives. The data contains gambling-specific information including:</p> <ul> <li>Demographics;</li> <li>Gambling attitudes and beliefs in gambling fallacies;</li> <li>Gambling participation; and</li> <li>Family history of problem gambling;</li> </ul> <p>In addition to gambling-specific data, the Online Panel Study contains general data variables including:</p> <ul> <li>Psychological factors (personality, mental health); and</li> <li>Comorbid factors (behavioural addictions, substance use, PTSD)</li> </ul> <p>A sample of 10,199 participants were recruited from each province of Canada. Participants were recruited through the Leger Opinion's registered pool of online participants. The LEO participant pool is structured to be demographically and geographically representative of the Canadian adult (18 years and older) population. Of the initial 10,199 participants, 4,707 participated in the follow-up survey. LEO registered participants were sent an email asking if they participated in gambling activities once per month. Participants who did gamble and consented to participating in the study were directed to an online survey. The baseline data was collected between August 2018 and October 2018. The follow-up data was collected between August 2019 and November 2019. Additional information on sampling, retention, study variables, and survey questionnaires can be located in the accompanying user manual and codebooks.</p> <p>The manual and codebooks were created by Dr. Carrie A. Shaw (née Leonard).</p>

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.063
GPT teacher head0.318
Teacher spread0.255 · 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

Quick stats

Citations3
Published2022
Admission routes2
Has abstractyes

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