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Record W6930730685 · doi:10.5281/zenodo.15847403

The image of Education in the daily electronic press

2022· book-chapter· en· W6930730685 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsReproductionPoliticsQuarter (Canadian coin)Period (music)Presentation (obstetrics)Meaning (existential)

Abstract

fetched live from OpenAlex

This paper highlights the role of communication as a two-way act of reproduction of dominant political tendencies, beliefs, but also the creation of tautological characteristics. The presentation methodologically with the thematic Content Analysis, as enriched by the contemporary literature, approaches the semantics, but also the meaning of the reproduction of the image of education. The period under consideration is the first quarter of 2013, a period in which important issues for education as a whole are in progress. At the same time, the construction of the image of education by the press through the mediation of communication mechanisms is highlighted. It also highlights the reproduction of the necessary political consensus on one of the major issues that preoccupied the educational and academic community in the first quarter of 2013: the "Athena Plan".The conclusions emphasize the construction of the image of education by the electronic press, as it is mediated by the mechanisms of communication, but also the reproduction of the necessary political consensus, through the sample of the electronic press examined, on one of the major issues that preoccupied the educational and academic community in the first quarter of 2013.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.008
Scholarly communication0.0080.005
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.011
GPT teacher head0.248
Teacher spread0.236 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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