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Record W4283789793 · doi:10.6007/ijarped/v11-i2/10752

The Age of Uncertainties: Why (?) is it so Difficult to Understand?

2022· article· en· W4283789793 on OpenAlexaff
Nur Aimi Nasuha Burhanuddin, Denise J. Larsen, Rozita Radhiah Said, Soaib Asimiran

Bibliographic record

VenueInternational Journal of Academic Research in Progressive Education and Development · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Alberta
FundersUniversiti Putra Malaysia
KeywordsComputer science

Abstract

fetched live from OpenAlex

Unannounced emergence of Covid19 has created chaos to the entire world, with none were left unaffected by this unseen but lethal microorganism.No one would have thought in this 21st century, humankind regardless of nationality, races, religious beliefs, etc. would have to go through a war with the unseen.In this trying time, one thing becomes apparent, it is important how we interpret things that happened around us.Schools and university are closed.Businesses are suspended.The debate about how people are going to survive in the next few months seems to reach no end as no one is prepared for this circumstance.Reflecting from my doctoral student research work, I elucidate the ways in which I try to understand participants' worldview through phenomenological design and link it with what is currently happening in the world through Husserl Transcendental Phenomenology and Heidegger Hermeneutics Phenomenology.

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)0.020
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.049
Scholarly communication0.0160.032
Open science0.0020.009
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0030.001

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 head0.359
GPT teacher head0.551
Teacher spread0.192 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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