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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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.359
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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