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Record W3213003236 · doi:10.36198/9783838554655

Argumentieren mit Statistik

2021· book· de· W3213003236 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typebook
Languagede
FieldArts and Humanities
TopicSports Science and Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhilosophyHumanitiesPhysics

Abstract

fetched live from OpenAlex

Endlich verstehen, wie Statistik funktioniert! Noch keinen Überblick im Bereich der statistischen Methoden? Dieser Band hilft! Die Autoren stellen verschiedene statistische Methoden anschaulich vor und erklären, wie man mit statistischen Ergebnissen in den Sozialwissenschaften methodisch haltbar argumentiert. Beispiele verdeutlichen, welche statistische Methode im jeweiligen Fall wie anzuwenden ist. Die verwendeten Beispiele können direkt am eigenen PC nachgerechnet werden - die hierfür verwendeten Daten stehen zur freien Verfügung. Mit dieser fundierten Vorbereitung lässt sich die Vielzahl statischer Methoden nicht nur erschließen, sondern direkt selbst anwenden. Dieses Buch eignet sich für alle Studierende aus den sozialwissenschaftlichen Fächern, die kompetent mit Statistik arbeiten möchten (und müssen).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, 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 score0.325
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.3330.008

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 head0.035
GPT teacher head0.249
Teacher spread0.214 · 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

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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