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Record W2794949905 · doi:10.5430/wje.v8n2p46

Evaluation of Human Rights, Citizenship and Democracy Course by Teacher's Vision

2018· article· en· W2794949905 on OpenAlexvenueno aff
Gülsün Şahan, Ayşegül Tural

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipDemocracyHuman rightsPhenomenology (philosophy)Citizenship educationQualitative researchSociologyGood citizenshipPedagogyPolitical scienceMathematics educationPsychologyLawSocial scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Human Rights, Citizenship and Democracy Course draws attention to with topics such as human rights, effectivecitizenship. In terms of content, it has an important place in contemporary education concept. It is thought that theHuman Rights, Citizenship and Democracy course will benefit the social structure because of its content and theoutputs that can be obtained at the end of the teaching process. The purpose of this research is to examination theopinions of teachers on the fourth class Human Rights, Citizenship and Democracy course. For this purpose,phenomenology from qualitative research methods were used in the study. As a result of the research, it was found thatteachers had positive opinions about Human Rights, Citizenship and Democracy lesson. The results obtained includestatements that administrators should have support for this course and the course should not be graded.

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)0.008
metaresearch head score (Gemma)0.020
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 score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.049
GPT teacher head0.450
Teacher spread0.401 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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