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Record W4382990403 · doi:10.26577/jgem.2023.v69.i2.02

HISTORICAL-GEOGRAPHICAL ASPECTS OF SUSTAINABLE DEVELOPMENT OF SMALL TOWNS (ON THE EXAMPLE OF SMALL TOWNS IN ZHAMBYL REGION)

2023· article· en· W4382990403 on OpenAlexaboutno aff
D.T. Aliaskarov, Kulyash Kaimuldinova, Shakhislam Laiskhanov, Nursultan Salimzhanov

Bibliographic record

VenueJournal of Geography and Environmental Management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsIndustrialisationSustainable developmentGeographyRegional scienceLimitingEconomic geographyEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The problems of sustainable development of small towns were analyzed from the perspective of historical-geographical factors in this article. During the analysis, we were convinced that monoprofile towns, which are part of the group of small towns, have become the "center" of problems in the world and the country. Theoretical and conceptual analysis of the concepts, names, opinions and conclusions of scientists developed in relation to these cities associated with global industrialization was carried out. The main mechanisms of rehabilitation and support of labor resources in monoprofile towns in a crisis situation were determined on the basis of the experience of the USA, Canada, Australia, Japan, Germany and other countries. And in the conditions of our country, we considered on the example of small towns in Zhambyl region. According to it, the historical aspects of specialization of small towns were given importance, classification of common issues limiting sustainable development was compiled. Demographic problems in towns were analyzed, and the place at the strategic stage of the development of innovative city was determined on the basis of historical data and theoretical conclusions. According to the concept of sustainable development, the main areas of urban environment development were selected, and their social, economic and environmental effects were emphasized. In general, the results of the study in the article will complement research in the field of urban geography.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.214
Teacher spread0.187 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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