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Record W4402679937 · doi:10.63051/kos.2024.3.83

STUDYING KAZAKH NECROTOPONYMS MONGOLIA AND KAZAKHSTAN (SECOND HALF XIX - FIRST QUARTER OF THE XXI CENTURIES)

2024· article· en· W4402679937 on OpenAlexaboutno aff
Baglan Baglan, Bimurad Burkhanov

Bibliographic record

VenueĶazaķstan šyġystanuy. · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKazakhQuarter (Canadian coin)Ancient historyInner mongoliaHistoryGeographyChinaArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract. The article is devoted to the study of funeral monuments (nektrotoponyms) of the Kazakhs of Kazakhstan and the western regions of Mongolia, where the overwhelming majority of the Kazakhs of this country currently live. Various kinds of expeditions organized during this period collected extensive material on the history, geography, ethnography, as well as toponymy of Mongolia and Kazakhstan. Moreover, in the context of the topic we are considering, it should be especially noted that scientific expeditions and trips of individual researchers were not of a special toponymic nature, but were carried out as part of a general study of history, geography, Mongolia and Kazakhstan. At the same time, the purpose of this article is to analyze the content and main directions of studying necrotoponyms of Kazakhstan and the western regions of Mongolia. When writing the work, the methods of factor and diachronic analysis, as well as the synthesis method, were used. In the course of studying this issue, the author came to the conclusion that the study of Kazakh necrotoponyms was carried out as part of a study of the traditional culture of the Kazakhs, in particular, funeral rites. The collected material shows that in traditional Kazakh society necrotoponyms performed various purely practical and ethnocultural functions. In particular, we are talking about the functions of preserving the historical memory of the population (memory of historical events), orienting people on the ground during their movement across vast steppe spaces, marking the limits of the ancestral territories of the Kazakhs, etc.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.214
Teacher spread0.193 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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