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Record W2007854472 · doi:10.5539/jedp.v3n2p168

Philosophical Thought in Education as an Approach across Disciplines in All Natures of Knowledge

2013· article· en· W2007854472 on OpenAlexvenueno aff
Aminuddin Hassan, Norhasni Zainal Abiddin, Sim Kuan Yew

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Subject (documents)CurriculumVocational educationSociologyPhilosophy of educationEpistemologyPhilosophy and economicsSocial sciencePolitical sciencePedagogyHigher educationLawPhilosophy

Abstract

fetched live from OpenAlex

It is important to understand the concept of philosophical thought within all natures of knowledge well. Thiswriting attempts to explore the perspective of the philosophy of education in Home Economics subjects. As withany other educational disciplines, the subject of Home Economics which is a part of the curriculum in Malaysiahave a clear direction and strategy in realizing the nation's desire to produce balanced and highly skilled humanresources. Home Economics is not a trashy subject to be underestimated because, ironically, it supports thephilosophy and ideals towards the nation's ambition. Without philosophy, there is no path that can be used as aguide to strengthen the actions and direction of educational philosophy. Without that support, the struggle oftechnical and vocational education cannot provide an impact on the industry and accomplish the aspirations ofthe nation as a whole. From the perspective of philosophy, the arguments in explaining the importance ofknowledge of Home Economics will also be discussed in this paper.

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)0.013
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0070.064
Scholarly communication0.0140.012
Open science0.0010.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.460
Teacher spread0.395 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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