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Record W4296654843 · doi:10.5539/ies.v15n5p36

The Examination of the Use of Media Content in Turkey’s Social Studies Textbooks in Light of UNESCO’s MIL’s Curriculum

2022· article· en· W4296654843 on OpenAlexvenueno aff
Erkan Şenşekerci

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedia literacyThematic analysisSocial mediaContent analysisContext (archaeology)SociologyDiversity (politics)PedagogyQualitative researchLibrary scienceSocial sciencePolitical scienceGeography

Abstract

fetched live from OpenAlex

This study aims to analyse the media excerpts found in the officially approved textbooks for the social studies course in Turkey from the perspective of the thematic areas included in UNESCO MIL’s [Media and Information Literacy] Curriculum. In the study, the descriptive analysis method was applied and the data were collected using document analysis. In order to determine whether the examined media excerpts contribute to the UNESCO’s MIL Curriculum achievements defined for these thematic areas, 11 research questions were prepared. In the first stage of the study, a checklist was prepared based on an examination of the UNESCO MIL’s Curriculum. In the second stage, the textbooks to be analysed were selected by the convenience sampling method, taking into account the textbook production policy carried out under the authority of the Ministry of National Education. The study, which examined 6 different textbooks approved for the 5th, 6th and 7th grades of secondary school, revealed that although the media excerpts are sufficient in number, they fail to reflect the diversity in the national and/or regional media. Moreover, these media excerpts are utilised primarily for the specific purposes of the course, and, naturally, they do not make a significant contribution to media literacy education. In conclusion, the reviewed media excerpts hardly meet the criteria for the thematic areas upon which UNESCO MIL’s Curriculum is based. Within the context of the findings and conclusions of the study, a set of recommendations has been shared with people and institutions operating in the fields of social studies textbooks and media literacy.

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)0.002
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.397
GPT teacher head0.459
Teacher spread0.062 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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