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Record W2786815979 · doi:10.22215/etd/2015-11193

Novelty vs. Predictability: Relationship Tensions in Close Relationships

2015· dissertation· en· W2786815979 on OpenAlexaff
Janelle Lebreton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsNoveltyBoredomPredictabilityPsychologySocial psychologyQuality (philosophy)DialecticCognitive psychologyMathematics

Abstract

fetched live from OpenAlex

The goal of this research is to examine relationship challenges and outcomes to experiences of both internal and between-person relationship tensions in novelty and predictability.Consistent with the dialectical model, I predicted that internal and between-partner tensions would be associated: a) more with the challenge of boredom than conflict, b) more with trying novel activities than familiar ones, and c) with reduced relationship quality.These hypotheses were assessed in two studies.In Study 1, a correlational design was employed where participants in long-term close relationships completed questionnaires related to personal relationship tensions, challenges, activity engagement, and relationship quality.In Study 2, I extended my analysis by using an experimental design to examine the effects of perceived tensions between partners in participants own relationships on challenges, activities, and relationship quality.Additionally, in Study 2, I examined the effect of goal orientation (approach, avoidance) in shaping these associations.

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)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.429
Teacher spread0.347 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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