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Record W4393494223 · doi:10.1080/24732850.2024.2336592

Reliability and Validity of the Measure of Life Priorities: A Questionnaire Based on the Good Lives Model

2024· article· en· W4393494223 on OpenAlexaff
Alexandra M. Zidenberg, Leigh Harkins, Kristina Shatokhina, Danielle M. Loney

Bibliographic record

VenueJournal of Forensic Psychology Research and Practice · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsRoyal Military College of CanadaOntario Tech University
Fundersnot available
KeywordsMeasure (data warehouse)Reliability (semiconductor)Reliability engineeringPsychologyValidityComputer scienceApplied psychologyManagement sciencePsychometricsEngineeringData miningClinical psychologyPhysics

Abstract

fetched live from OpenAlex

This study examined the reliability and validity of the “Measure of Life Priorities” (MLP) which was developed to ascertain a person’s Good Lives Model (GLM) goods. The MLP was validated against a number of relevant constructs, and the test-retest reliability of the measure was evaluated. The MLP had acceptable reliability for both Importance (α= .694) and Achievement (α= .733) of the goods. Most items demonstrated moderate test-retest reliability (ICCs from .52 to .74) and an overall trend demonstrating that items focused on Importance appeared more reliable. The implications include broadening the settings in which the GLM can be studied.

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)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
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 integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.445
Teacher spread0.295 · 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 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
Published2024
Admission routes1
Has abstractyes

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