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Record W4236773680 · doi:10.2489/63.3.76a

Trends in soil science education: Looking beyond the number of students

2008· article· en· W4236773680 on OpenAlexaboutno aff
Alfred E. Hartemink, A. McBratney, Budiman Minasny

Bibliographic record

VenueJournal of Soil and Water Conservation · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFellScience educationMathematics educationSociologyPsychologyGeography

Abstract

fetched live from OpenAlex

Decreasing student numbers—along with related causes and concerns—is a common topic of discussion in the international soil science community. Such discussion is seldom quantitative. Here we present long-term student numbers (in undergraduate courses as well as MS and PhD graduates) of soil science departments in North America, Europe, and Oceania. A previous study by P. Baveye and co-workers had shown that in the United States and Canada student numbers fell by 40% in more than 80% of the universities between 1992 and 2004. The United States and Canada experienced an increase in female students in soil science between 1992 and 2004. Meanwhile, the number of foreign students has decreased. Student numbers have also decreased in New Zealand. Numbers at Dutch universities decreased in the early 1990s but have since stabilized. Two of three Australian universities had increasing numbers of students for undergraduate courses as well as MS and PhD graduates. Currently in the Netherlands almost half of all MS soil science graduates are female, while in the 1970s and up to the mid-1980s 80% or more of soil science graduates were male. It seems that teaching is becoming more general (more introductory courses to a range of other disciplines), while …

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.096

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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2008
Admission routes1
Has abstractyes

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