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Record W7135921515

Kan retsvidenskaben være empirisk?:Om aktualiteten af Alf Ross’ empiriske vending i retsfilosofien

2013· article· da· W7135921515 on OpenAlexaff
Jakob von Holderstein Holtermann, Mikkel Jarle Christensen, Mikael Rask Madsen

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2013
Typearticle
Languageda
FieldSocial Sciences
TopicComparative and International Law Studies
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsLegal history
DOInot available

Abstract

fetched live from OpenAlex

Med udgangspunkt i Alf Ross’ retsrealistiske projekt beskæftiger denne artikel sig med, om retsvidenskaben er en disciplin i sin egen ret, eller om den i sidste ende er en del af samfundsvidenskaben særligt sociologien. Konkret undersøges dette skisma hos Ross gennem hans kritik af Theodor Geigers retssociologiske arbejder, hvor Ross imod Geiger argumenterer for, at retsvidenskaben uanset ambitionen om at blive empirisk stadig må være principielt forskellig fra retssociologien. I artiklen argumenteres der for, at denne påstand er uholdbar, og at den bl.a. hviler på en vilkårlig afgrænsning af sociologien, både hvad angår dens metode og dens genstand. Artiklens konklusioner har samtidig betydning for, hvilke udviklingslinjer man vælger at tegne fra Ross’ egen realistiske retslære i midten af forrige århundrede og frem imod vore dages iøjnefaldende empiriske vending i retsvidenskaben kendetegnet ved bevægelser som New Legal Realism, Empirical Legal Studies, Law and Economics og forestillingen om en naturalisering.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0060.005
Scholarly communication0.0000.002
Open science0.0040.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.5620.144

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 head0.132
GPT teacher head0.366
Teacher spread0.233 · 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
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
Published2013
Admission routes1
Has abstractyes

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