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Record W3035767339 · doi:10.32370/ia_2020_06_8

Organizational and Pedagogical Conditions of Future Social Workers’ Professional Training for Social Leadership

2020· article· en· W3035767339 on OpenAlexvenueno aff
Daria Bybyk

Bibliographic record

VenueIntellectual Archive · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance (law)Professional developmentQuality (philosophy)Social workPsychologyTraining (meteorology)Vocational educationResource (disambiguation)Public relationsSociologyEngineering ethicsPedagogyPolitical scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

This article is devoted to the study of the need to improve the scientific and methodological support for the professional training of future social workers. Relevance determined the choice of research objectives: to identify the forms and methods of implementing the preparation of future social workers for social leadership. It was determined that social leadership is the main resource that provides a holistic view of the modern specialist, who should not only be prepared for future professional activity, but also be able to navigate independently in the stream of socio-economic changes, creatively solving professional tasks of social work. Particular attention is concentrated on the features of the use of forms and methods of training social workers. This is noted the prospects of the ideas of social leadership in the development and implementation of the scientific and methodological complex, the success of which is determined by the need to find new ways to improve the quality of theoretical training, the ability to work independently, and professional self-development of students. Non-traditional forms and interactive methods of vocational teaching students provide enhanced training opportunities for social leadership.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.446
GPT teacher head0.453
Teacher spread0.007 · 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 designQualitative
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

Citations5
Published2020
Admission routes1
Has abstractyes

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