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Record W2075721869 · doi:10.1027/1866-5888/a000084

Development and Initial Validation of the Workplace Resilience Inventory

2013· article· en· W2075721869 on OpenAlexaff
Matthew J. W. McLarnon, Mitchell G. Rothstein

Bibliographic record

VenueJournal of Personnel Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyPsychological resilienceMeasure (data warehouse)Life satisfactionInternal consistencySocial psychologyConstruct validityResilience (materials science)PsychometricsApplied psychologyClinical psychology

Abstract

fetched live from OpenAlex

This study sought to provide the initial psychometric evidence supporting a new measure of resiliency. In consideration of the shortcomings of previous measures, a more comprehensive measure was developed based on the theoretical model of King and Rothstein (2010) . The resulting measure, the Workplace Resilience Inventory (WRI), encompasses an individual’s personal characteristics, social support network, initial responses to a significant and life changing event, and self-regulatory processes. Following a rigorous, theoretically-based, and empirically-supported procedure for selecting items, the facets of the WRI demonstrated acceptable internal consistency, as well as adequate independence. The WRI demonstrates significant relations with important well-being criteria, such as satisfaction with life, depression, and perceived stress, and demonstrates incremental validity above and beyond a previously validated measure of resiliency, the Psychological Capital (PsyCap) questionnaire.

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)0.016
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.396
Teacher spread0.346 · 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 designBench or experimental
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

Citations154
Published2013
Admission routes1
Has abstractyes

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