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Social animations as a technology of integration of youth with disabilities

2021· article· en· W3167221917 on OpenAlexaboutno aff
Olha Boiko, Вікторія ІСАЧЕНКО

Bibliographic record

VenueSocial work and social education · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPsychology

Abstract

fetched live from OpenAlex

A brief analysis of different approaches to the definition of «animation», in particular in terms of economics, psychology, pedagogy and social work. The role and place of social animation in creating an environment in which each individual will be able to successfully develop and self-realize for the benefit of society. A comparison of approaches to the use of social animation in foreign countries. In particular, the experience of the USA, Canada, France and Finland is analyzed. The latest researches and publications on the problem of social animation of youth in Ukraine are analyzed. It was found that the main directions of social animation work are overcoming personal tendencies to social disintegration (prevention of socio-psychological disorders, such as deviant behavior of adolescents, drug addiction, alcoholism, suicide, etc.); rehabilitation of critical states of personality; assistance in creative self-realization of the individual. The scope of professional activity of a social worker in the field of social animation is defined. The peculiarities of social animation with young people with disabilities are considered, and it is found that social animation with young people with disabilities overcoming socio-psychological isolation. Social animation allows to create conditions for personal growth and productive interpersonal communication in the process of leisure, directs to socially significant activities. The positive consequences of the organization of social animation with young people with disabilities are highlighted. Social animation allows to create conditions for personal growth and productive interpersonal communication in the process of leisure, directs to socially significant activities.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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