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Record W4393176845 · doi:10.17159/sajs.2024/16059

Selection, sequencing and progression of content in biology in four diverse jurisdictions

2024· article· en· W4393176845 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSouth African Journal of Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsSelection (genetic algorithm)BiologyComputational biologyPositive selectionEvolutionary biologyBiotechnologyGeneticsComputer scienceGeneArtificial intelligence

Abstract

fetched live from OpenAlex

Selection of content for a school syllabus is important in achieving progress towards inclusive generalisations which characterise powerful knowledge. Biology as a discipline progresses from knowledge of individual facts to inclusive generalisations such as homeostasis, energy transformations, heredity, and evolution. The present study evaluated the selection of content in the official biology syllabus for the seventh and eighth years of schooling in four diverse jurisdictions: Kenya, South Africa, British Columbia (Canada) and Singapore. The purpose was to determine whether and how content selection enabled progression to inclusive generalisations in biology and to compare selection, sequencing and progression among the four jurisdictions. General Topic Trace Mapping was used to compare each syllabus to a generic reference syllabus structured according to inclusive generalisations. Although there was some agreement in the scope of topics selected, jurisdictions varied in the way it was organised. Kenya included more everyday knowledge than other jurisdictions. British Columbia and Singapore selected content according to unifying themes, whereas South Africa and Kenya did not. South Africa selected content that enabled progression towards inclusive generalisations, but did not explicitly identify the generalisations. This study supports the contention that powerful knowledge in biology may be construed differently in diverse jurisdictions.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.038
GPT teacher head0.322
Teacher spread0.284 · 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