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Record W7120545116

Structure and dynamics of families in the late life cycle stage and intellectual disability

2017· article· pt· W7120545116 on OpenAlexaboutno aff
Renata Balieiro [UNIFESP] Takebayashi

Bibliographic record

VenueUNIFESP Institutional Repository (Universidade Federal de São Paulo) · 2017
Typearticle
Languagept
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual disabilityFeelingNoticeThematic analysisQualitative researchPerceptionGenogramFace (sociological concept)Social isolation
DOInot available

Abstract

fetched live from OpenAlex

To know and understand the dynamics of a family including a member with Intellectual Disability in the late life cycle stage. Method: This was a qualitative clinical study. Ten families that took part in semistructured interviews were chosen. The interviews were complemented with genograms and ecomaps, and then content and thematic analysis was performed. The Systems Theory was used as theoretical referential and the Calgary Model for Family Evaluation (MCAF), as the methodologic referential. Results: Based on interviews with families, the following categories were developed: Family’s interaction with Intellectual Disability; Communication as a family strategy to share feelings and notice the other person; The perception of family isolation and the need of external aid; Family’s concern about future care: aging and death; and Interview as a tool to increase family communication and future reflections. Conclusion: Families including a person with Intellectual Disability face changes in their dynamics, structure and organization; they deal with difficulties regarding the social inclusion of the person with Intellectual Disability; and use specific mechanisms of communication and support search, in addition to the suffer they face towards future projections

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.292
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

Explore more

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