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Стратегически фактори в средата на училищните организации

2016· article· W7128439095 on OpenAlexaboutno aff
Динко Господинов

Bibliographic record

VenueГодишник на Софийския университет "Св Климент Охридски" Факултет по педагогика Книга Педагогика · 2016
Typearticle
Language
FieldMathematics
TopicAdvanced Research in Science and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Work (physics)Curriculum

Abstract

fetched live from OpenAlex

Изследването е посветено на проблема за стратегическите фактори в организационната среда на училищните организации. Направен е опит за конкретизиране на тези фактори. В студията се прави кратка характеристика на различните фактори. Библиография: България 2020. Институт за пазарна икономика, 2015. - www.ime.bg - посетен на 11.01.2016. Глоссарий современного образования. Харков, 2014. НУА. Господинов, Д. Организационният контекст и управлението на човешките ресурси в училище. - ГСУ „ Св. Климент Охридски ", Факултет по педагогика, Книга Педагогика, т. 102, 2009. Еничарова, Е. Образователна политика и законодателство. С., 2015. Закон за предучилищното и училищното образование. Захариев, Б., И. Йорданов. Оценка на включването на ромите на пазара на труда чрез общи и специфични за целевата група мерки и програми за заетост, финансирани от ЕС. Институт „Отворено общество“, 2014. - www.osf.bg - посетен на 12.01.2016. Как България може да подобри образованието си? Световна банка - България, 2014 - посетен на 12.01.2016. Национална стратегия на Република България за интегриране на ромите 2012-2020 г. Преброяване на населението 2011 година. Окончателни резултати. Национален статистически институт. - www.nsi.bg - посетен на 10.01.2016. Регионални профили - показатели за развитие 2015 г. Институт за пазарна икономика, 2015 г. - www.irae.bg - посетен на 14.01.2016. Шведовская, А., Т. Загвоздина. Социально-зкономический статус семьи и психическое развитие ребенка: зарубежньгй опит. - Психологическая наука и образовате, 2013, 1. - http://psyjournals.ru/psyedu/2013/nl/58600_full.shtmlp - посетен на 15.01.2016. Bascia, N. The School Context Model: How School Environment Shape Students Opportunities to Learn. University of Toronto, 2014. Branson, C., S. Gross. Handbook of Ethical Educational Leadership. New York, 2014. Routledge. Bulgaria Teachers. SABER Country Report, 2013. - www.worldbank.org Cletus, В., F. Lunenburg, L. Potter. Creating for High-Performing Schools. New York, 2011, Rowman & Littlefield Education. Delaney, J. Educational Policy Studies. Brush Education, 2015. Eulina, M., P. de Carvalho. Rethinking Family - School Relations. New York, 2014, Psychology Press. Glanz, J. Cultural Leadership. Corwin Press, 2006. Handbook of Resilience in Children. Springer, 2013. Handbook of Prosocial Education. 2011 Rowman & Littlefield Education OFSTED Criteria of the Strategic Analysis for School, 2011. - www.boltonlea.org.uk Rizvi, Е, B. Lingard. Globalizing Educational Policy. New York, 2010, Routledge. UNESCO Handbook of Education Policy Analysis and Programming. Vol. 2. UNESCO, 2013. Zajda, J., M. Geo-Jaja. The Politics ofEducation Reforms. Springer, 2010.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.008
Scholarly communication0.0150.008
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0500.019

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 head0.097
GPT teacher head0.387
Teacher spread0.290 · 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 designNot applicable
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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