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Record W4390104913 · doi:10.33524/cjar.v22i3.641

CARN – D.A.CH. Conference 2023

2022· article· en· W4390104913 on OpenAlexvenueno aff
CJAR

Bibliographic record

VenueThe Canadian Journal of Action Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSociology and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermanAction researchAction (physics)Library scienceSociologyMedia studiesPedagogyComputer scienceArchaeologyHistoryPhysics

Abstract

fetched live from OpenAlex

The 10th CARN D.A.CH. conference will be held at the University College of Teacher Education Styria (Austria) on the 9th & 10th of February, 2023. All those interested in discussing action research in German are very warmly welcome. To submit an abstract and/or register, please see the Conference Flyer, linked below. CARN D.A.CH. is a German-language Action Research network and part of the international Collaborative Action Research Network (CARN). Click to view the Conference Flyer See full annoucement in PDF attachment.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.570
GPT teacher head0.547
Teacher spread0.024 · 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.

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
Published2022
Admission routes1
Has abstractyes

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