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Record W2542734186 · doi:10.5539/ies.v9n11p40

Preschool Teachers’ Views on Schools’ Indoor and Outdoor Environment Safety

2016· article· en· W2542734186 on OpenAlexvenueno aff
Tuğba Konaklı, Esra Ulcetin

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyResearch designDescriptive statisticsData collectionWork (physics)Class (philosophy)Mathematics educationStairsResearch dataMedical educationPedagogySociologyEngineeringComputer scienceMathematicsStatisticsMedicine

Abstract

fetched live from OpenAlex

<p class="apa">The aim of this research is to analyze opinions of teachers who work in preschool education institutions concerning precautions that should be taken for indoor and outdoor security. Study group of this research is determined by criterion sampling from purposeful sampling techniques. The study group of this research is consist of eight preschool teachers who work in four private and four public schools in Kocaeli İzmit district in the fall semester of 2013-2014 Academic Year. For the purpose of the research, data are collected with semi-structured interview technique. During the research, the interviews are recorded with tape recorder and the interviews are put down on paper then analyzed. After the recorded data are submitted to approval of participants, the analysis of the data has started. Date are analyzed with descriptive analysis method and coded then interpreted. In order to ensure validity of the research, the data are tried to be analyzed with direct quotes of the participants. Research findings show that the most important risk factors are caused by defective design of schools. Research results also show that schools have not only indoor security problems such as stairs and door but also external security problems such as garden and playgrounds.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.134
GPT teacher head0.365
Teacher spread0.231 · 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 teacher head, not a consensus.

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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