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Record W6989426131

Att bygga broar - kulturella, språkliga och mediala möten

2010· other· sv· W6989426131 on OpenAlexfundno aff

Bibliographic record

VenueMalmö University Publications (Malmö University) · 2010
Typeother
Languagesv
FieldSocial Sciences
TopicSocial and Educational Sciences
Canadian institutionsnot available
FundersMalmö HögskolaYork UniversityKarlstads universitetUniversity of Notre DameAlexander von Humboldt-Stiftung
Keywordsnot available
DOInot available

Abstract

fetched live from OpenAlex

Nationella nätverket för svenska med didaktisk inriktningDen 1 januari 2003 startade det nationella nätverket för forskning och forskarutbildning i svenska med didaktisk inriktning (SMDI) med Malmö högskola som värdlärosäte.Nätverket uppstod i det samarbete som skapats mellan tretton av landets lärosäten för att bedriva en nationell forskarskola i svenska med didaktisk inriktning.Nätverket har till syfte att:• verka för tillväxten av forskning och forskarutbildning • stimulera utvecklingsprojekt inom fältet • underlätta kontakter och informationsutbyte mellan verksamma forskare samt mellan forskare och lärare i skolan• organisera årlig konferens Årligen anordnas nätverksmöten och en forskningskonferens.Rapporter från konferenserna publiceras i nätverkets skriftserie Texter om svenska med didaktisk inriktning.Årets forskningsrapport har fått stöd från Lärarutbildningens forskningsnämnd vid Malmö högskola och SMDI/Malmö.För detta är vi mycket tacksamma.Med denna volym har hittills sju antologier publicerats.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.165
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.002
Scholarly communication0.0080.002
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1650.035

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 head0.234
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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