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Record W7059598490

[no title]

2024· other· en· W7059598490 on OpenAlexfundno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2024
Typeother
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
FundersUniversity of the Western CapeInternational Development Research CentreU.S. Department of Agriculture
KeywordsAgricultureProduct (mathematics)Government (linguistics)Environmental degradationConventionLocal government
DOInot available

Abstract

fetched live from OpenAlex

In the same way that South Africa’s people were divided along racial lines, so too was its landscape – into the predominantly communally farmed lands of the homelands and self-governing territories, and commercial farming areas. These divisions, reflected both in former government policy and local practice, have profoundly affected land degradation in South Africa. This book, the product of extensive research, is based on a landmark report on land degradation arising from South Africa’s commitment to the UN Convention to Combat Desertification. It reflects the first complete assessment of South Africa’s land degradation problem, taking into account not only agricultural and ecological concerns, but also the socio-political and historical contexts. It places previously unavailable information in the hands of those who need it most – politicians, agricultural extension officers, and communal and commercial farmers. It will also be of interest to students and teachers. At once sobering, challenging and optimistic, this book is a call to action. It shows that we are all affected by the extent of land degradation in South Africa.

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 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 categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0030.002
Open science0.0060.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0400.001

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 head0.056
GPT teacher head0.382
Teacher spread0.326 · 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; both teacher heads agree on what is shown here.

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

Explore more

Same venueDirectory of Open access Books (OAPEN Foundation)Same topicMagnetic Field Sensors TechniquesFrench-language works237,207