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Record W7037215953

"De mektige mederne" Samfunnsstruktur og identitet i Media i perioden 836-550 f.Kr.

2016· dissertation· no· W7037215953 on OpenAlexaboutno aff

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2016
Typedissertation
Languageno
FieldArts and Humanities
TopicAncient Near East History
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Quarter (Canadian coin)Patron saint
DOInot available

Abstract

fetched live from OpenAlex

I denne oppgaven har jeg tatt for meg samfunnsstruktur og identitet i Media i tidsperioden 836–550 f.Kr. Utgangspunktet har vært å se på assyriske, babylonske og akamenidiske kilder, for å kartlegge typiske trekk ved det mediske samfunnet. Jeg har redegjort for medisk identitet på ulike nivåer i samfunnet. Personlige karakteristikker, bosetning, økonomi, politisk struktur, religion og materiell kultur, er de mest sentrale aspektene som drøftes i dette studiet. Når det gjelder kildene er det lagt mest vekt på assyriske kilders fremstilling av mederne, og det er i lys av disse fremstillingene at de babylonske og klassiske kildene diskuteres. Med grunnlag i ulike kjennetegn tilskrevet mederne og deres samfunn, har jeg forsøkt å identifisere en særegen medisk identitet, til tross for en utfordrende kildesituasjon. Videre består oppgaven av en diskusjon rundt Herodots medikos logos i Historie og den tradisjonelle forståelsen av Media som et imperium, samt hvorfor Herodot ikke anses som en pålitelig kilde. Herodots beskrivelse av en prosess med etablering av et medisk dynasti er diskutert opp mot de assyriske kildene og om hvorvidt det på et tidspunkt ble etablert en medisk stat.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0040.005
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0330.007

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 head0.043
GPT teacher head0.268
Teacher spread0.225 · 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
Published2016
Admission routes1
Has abstractyes

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