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Record W3117072296

Douglas Mawson and the Nation of Science

2020· article· en· W3117072296 on OpenAlexaboutno aff
John Scheckter

Bibliographic record

VenueJournal of the Association for the Study of Australian Literature · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsModernityUncannyChampionSociologyField (mathematics)HistoryPolitical scienceLawAestheticsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In the early decades of the twentieth century, a nation’s participation in global communities of science denoted high degrees of cultural modernity. For Australia, the accomplishments of Douglas Mawson signified that national assertion. Unlike the arts, where lines of descent and influence remained important, scientists before 1914 frequently saw themselves without borders; this claim offered vast encouragement to newer societies, who found their champion in Ernest Rutherford, born in New Zealand and awarded the Nobel in 1908 for work in Canada. Australia – the new Federation and the progressive states – heartily grasped the opportunity, and Mawson personified that demonstration, particularly in Antarctica: in calling him ‘an Australian Nansen,’ Edgeworth David drew a sharp distinction between Mawson and his British compeers, Scott and Shackleton. Both Mawson and Nansen were field scientists of utmost rigor, who directed their celebrity toward public activism on behalf of a new nation (Australia, 1901; Norway, 1905). That newness, moreover, produced a modernity that Gyan Prakash calls ‘an uncanny double, not a copy, of the European original’ ( Another Reason 5); thus, while Mawson represented modern science in Australia, he also worked, consciously and originally, to reconfigure the global playing field of modernity altogether.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.014
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.304
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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