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Record W7108467334 · doi:10.14749/30775475

South African National Survey of Research and Experimental Development: key sector results and trends: higher education sector R&D at a glance. Fact sheet 39

2025· article· en· W7108467334 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

VenueHuman Science Research Council SA · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicProfessional Masters Programs Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHigher educationFact sheetWorkforceGovernment (linguistics)Quarter (Canadian coin)Further educationOvertaking

Abstract

fetched live from OpenAlex

South Africa's higher education (HE) sector plays a pivotal role in the national system of innovation-it houses the largest R&D workforce in the country with two-thirds of total R&D personnel working in this sector. This fact sheet shows that in 2019/20, higher education was responsible for 41.4% of total R&D spending in the country, overtaking business sector spending on R&D. The natural sciences, technology and engineering, and the social sciences continue to dominate higher education research. Researchers from other countries make up almost a quarter of the total in higher education, most of them postgraduate students.

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)0.092
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0920.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.010
Science and technology studies0.0020.004
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.610
GPT teacher head0.534
Teacher spread0.075 · 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