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Record W2992875128 · doi:10.15139/s3/hzdgwa

Ottawa Couples Diary Study, 2016

2019· dataset· en· W2992875128 on OpenAlexaffabout
Cheryl Harasymchuk, Amy Muise, Emily A. Impett

Bibliographic record

VenueOpen MIND · 2019
Typedataset
Languageen
FieldSocial Sciences
TopicMarriage and Sexual Relationships
Canadian institutionsUniversity of TorontoYork UniversityCarleton University
Fundersnot available
KeywordsBoredomClosenessDemographicsPsychologyDemographySocial psychologySociology

Abstract

fetched live from OpenAlex

We recruited 122 mixed-sex couples from Canada via online ads posted in five major Canadian cities (Reddit, Kijiji) and through advertisements posted in public locations in a major Canadian city. Couples were eligible to participate if they were in an exclusive, monogamous relationship for at least 2 years and were living together (couples were pre-screened for eligibility via email and telephone). <br> <br> Couple members each completed a background survey (approximately 55 minutes in length). Then, each couple member started the 21-day diary study on the same day. Each couple member completed 21 daily diaries in total. On average, participants completed 19.56 out of 21 days. We followed-up with each couple member 3-months later. <br> <br> Measures: <br> <br> At background, we assessed demographics, individual differences (e.g., attachment styles, Big Five, approach and avoidance relationship goals, self-esteem) and relationship and sexual experiences (e.g., closeness, commitment, satisfaction, social threats and rewards, self-expansion, conflict, boredom, sexual desire and satisfaction, compassionate love). <br> <br> At the daily level, we assessed relationship and sexual experiences (e.g., satisfaction, commitment, boredom, conflict, types of love, sexual desire and satisfaction). <br> <br> At the 3-month follow-up, we assessed relationship quality (e.g., satisfaction, thoughts of separation, boredom, self-expansion).

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.055
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0400.018

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 head0.130
GPT teacher head0.414
Teacher spread0.284 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes2
Has abstractyes

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