MétaCan
Menu
Back to cohort
Record W2151782399 · doi:10.1177/0022219414522705

Using a Multidimensional Measure of Resilience to Explain Life Satisfaction and Academic Achievement of Adults With Reading Difficulties

2014· article· en· W2151782399 on OpenAlexaff
Holly L. Stack‐Cutler, Rauno Parrila, Minna Torppa

Bibliographic record

VenueJournal of Learning Disabilities · 2014
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntrapersonal communicationPsychologyInterpersonal communicationPsychological resilienceReading (process)Academic achievementLife satisfactionResilience (materials science)Structural equation modelingInterpersonal relationshipDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

We assessed the impact of intrapersonal and interpersonal resilience, persistence, and number of difficulties in addition to reading problems on life satisfaction (general, social, and self) and academic achievement. A total of 120 adults with reading difficulties who either were completing a university degree or were recent graduates responded to an in-lab or online survey. Results indicated that intrapersonal resilience correlated positively with interpersonal resilience and persistence, and both resilience factors were negatively associated with number of difficulties. Using structural equation modeling, intrapersonal resilience explained general satisfaction, intrapersonal resilience and number of difficulties explained self satisfaction, and interpersonal resilience explained social satisfaction. Academic achievement did not correlate with any of the included variables.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.035
GPT teacher head0.355
Teacher spread0.319 · 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

Citations40
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Learning DisabilitiesSame topicResilience and Mental HealthFrench-language works237,207