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Record W2097281744 · doi:10.5539/ass.v10n21p250

Influence of Trainings on the Indicators of Sociopsychological Adaptation

2014· article· en· W2097281744 on OpenAlexvenueno aff
Akhmetzyanova Nataliya Viktorovna, Nugmanova Dzhamilia Renatovna

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
FundersKazan Federal University
KeywordsAdaptation (eye)PsychologyFeelingDuration (music)Test (biology)Applied psychologyTraining (meteorology)Social psychologyMathematics educationGeography

Abstract

fetched live from OpenAlex

The article deals with the singularities of influence of trainings on the processes of sociopsychological adaptationof students. The objective of the research is to study the singularities of influence of trainings on the change ofthe students' adaptation process indicators.The authors suggest an original psychological express test in the form of interrogation. The indicators ofsociopsychological adaptation were determined. The empirical study of changes of the adaptation processesindicators during the training was carried out, and the obtained results were analyzed. The fulfilled research gavereasons to conclude that the suggested hypothesis was valid, and that the training classes irregularly influence onthe changes of students' adaptation indicators. The strongest influence of the classes affected the change of theemotional comfort indicator. The change of the indicator of safety feeling in a group was of nature that was morecomplex. It depends on the duration of the training classes. When the duration is short, the variation indicatordecreases insignificantly, and the difference of the values before and after the trainings is not statistically valid.When carrying out the 4-day program, we observed statistically valid changes in the indicators, and the variationof changes in the indicators decreases more than six times (from 38.7% to 6.4%).Thus, the research showed high efficiency of the developed training program.The obtained results allow developing more efficient psychological trainings targeting sociopsychologicaladaptation. At the development, it is necessary to take into account the complexity of dealing with the indicatorsof safety in a group and self-esteem.

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)0.010
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.350
Teacher spread0.313 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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