MétaCan
Menu
Back to cohort
Record W1964085375 · doi:10.1111/1540-5826.00060

General and Specific Issues for Researchers’ Consideration in Applying the Risk and Resilience Framework to the Social Domain of Learning Disabilities

2003· article· en· W1964085375 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLearning Disabilities Research and Practice · 2003
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLearning disabilityPsychologyPsychological resilienceResilience (materials science)Intervention (counseling)PerceptionDomain (mathematical analysis)Applied psychologyDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

In this article, I discuss several general and specific issues that pertain to the risk and resilience framework. I propose that these issues deserve consideration by researchers using or interested in using the risk and resilience framework to guide their research in the social domain of learning disabilities. General issues discussed include: (1) integrating current research findings with those from prior longitudinal research by Emmy Werner and her associates, and from research in the 1980s and 1990s on problems in social perception and communication in children with learning disabilities; (2) measurement problems; and (3) the need for more differentiation in research regarding gender and the severity of learning disabilities. The specific issues discussed include: the need to continue to search for potential risk and protective factors; the need to research mediating processes or mechanisms that render a factor a risk or a protection; and the nature of intervention research.

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.

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)0.013
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.153
GPT teacher head0.513
Teacher spread0.360 · 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