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Record W4400575956 · doi:10.1002/9781394253326.ch9

Education, the Lighting of a Fire

2024· other· en· W4400575956 on OpenAlexaff
Anthea Kong, Jake Wyman, Doris Hiam‐Galvez

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsArchitectural engineeringEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

A more sustainable future is dependent upon the education we bestow the current generations today. Education serves as part of the foundation of DSP, as the investment of resources in developing lifelong skills will support long term societal, ecological and economic growth. However, education must be revamped from its traditional format to one with a greater focus on stimulating curiosity, learning from nature and prioritising practical life skills. Using the DSP framework, we can effectively determine the necessary skills to support a more sustainable future and reduce skill mismatches through the implementation of retraining and upskilling programmes.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.087
Threshold uncertainty score0.292

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0870.011

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 head0.019
GPT teacher head0.368
Teacher spread0.349 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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