MétaCan
Menu
Back to cohort
Record W3210115367 · doi:10.24908/iee.2021.14.2.e

The Little Prince is an ecologist

2021· article· en· W3210115367 on OpenAlex
Christopher J. Lortie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueIdeas in Ecology and Evolution · 2021
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAbsurdityAestheticsSociologyEnvironmental ethicsNatural (archaeology)Openness to experienceEcologyHistoryLiteratureArtPsychologyPhilosophySocial psychology

Abstract

fetched live from OpenAlex

Stories shape the human experience. Fairy tales, fables, and historical stories from many peoples influence contemporary culture and science. The Little Prince is an excellent example of a short tale that highlights the relative importance of living with ecology and connectedness. It also clearly illuminates the absurdity that can emerge when one becomes isolated from even the simple processes associated with the functioning of other natural systems or from ecological interactions. This is one of many excellent stories that can be used in teaching science to frame theory for learners into different and larger novel contexts. This fairy tale provides morals for daily living too--tend to your garden, watch sunsets, and use nature to tame your absurd life and connect to others. We use humour, stories, and current cultural memes from television and movies in many publications and/or their titles and in classroom lessons. Looking more broadly for tales and stories from different cultures and times promotes justice and openness.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.319
Teacher spread0.293 · 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