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Record W2613925846 · doi:10.24043/isj.15

Toponymy and nissology: an approach to defining the Balearic Islands’ geographical and cultural character

2017· article· en· W2613925846 on OpenAlexvenueno aff
Antoni Ordinas Garau, Jaume Binimelis Sebastián

Bibliographic record

VenueIsland Studies Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeological and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsToponymyBalearic islandsCharacter (mathematics)GeographyHistoryEthnologyLinguisticsCartographyArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

The cultural identity of each of the larger islands that make up the Balearic archipelago is shown through the local geographical terminology and toponymy, which are results of the successive overlapping of languages and cultures brought to the islands by various peoples throughout history.By classifying and analyzing the toponymy and geographical terminology of the Balearic Islands, unique particularities can be found.There are differences between each of the islands, as well as with non-island territory, as a result of centuries of isolation.This same isolation has also led to the preservation of terminology and other linguistic aspects, and has created an endemic culture.The results of the records of terminology that contribute to the geographical and cultural characterization of the Balearic Islands are presented along with some keys to understanding the islands' idiosyncrasies.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.009
Science and technology studies0.0040.021
Scholarly communication0.0070.007
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.080
GPT teacher head0.291
Teacher spread0.210 · 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 designQualitative
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

Citations2
Published2017
Admission routes1
Has abstractyes

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