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Record W4399688010 · doi:10.1007/s40751-024-00145-w

An Ode to a Mathematician: Commemorating Uri Leron

2024· article· en· W4399688010 on OpenAlex

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.

Bibliographic record

VenueDigital Experiences in Mathematics Education · 2024
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsSimon Fraser University
FundersTechnion-Israel Institute of Technology
KeywordsVariety (cybernetics)Mathematics educationOdeEditorial boardComputer scienceEpistemologyLibrary sciencePsychologyLiteraturePhilosophyArtificial intelligenceArt

Abstract

fetched live from OpenAlex

Abstract This is one of two contributions written to commemorate Professor Uri Leron, who became Associate Editor of what was then the International Journal for Computers and Mathematical Learning, a journal founded by Seymour Papert, and upon which Digital Experiences in Mathematics Education builds. One contribution includes memories from several current and former Editorial Board members. In this contribution, five former supervisees of Uri Leron share their stories. In addition to the personal and professional development of the storytellers, the stories reflect upon the distinguished career of Prof. Leron—a mathematician, an educator, a mentor and a colleague. These stories reflect a scholarly exchange devoted to the debate upon the nature of mathematical and computer science thinking and teaching. These topics are addressed from a variety of perspectives—cognitive, social and psychological—to highlight Uri’s interest in computing as a way to express and explore mathematical and logical ideas.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
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 head0.020
GPT teacher head0.331
Teacher spread0.311 · 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