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Record W3201423109

СИСТЕМА ІНДИКАТОРІВ УМОВ ПРОЖИВАННЯ НАСЕЛЕННЯ НА МІСЦЕВОМУ РІВНІ: ПРИНЦИПИ ФОРМУВАННЯ ТА ВИКОРИСТАННЯ

2021· article· uk· W3201423109 on OpenAlexaboutno aff
Uliana Leshenok, Tetiana Lukovych

Bibliographic record

VenueDemography and social economy · 2021
Typearticle
Languageuk
FieldEconomics, Econometrics and Finance
TopicLabor Market and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationNoveltyComponent (thermodynamics)Quality of life (healthcare)Relevance (law)BusinessComputer scienceGeographyPsychologyPolitical scienceSocial psychologyEnvironmental healthMedicine
DOInot available

Abstract

fetched live from OpenAlex

The relevance of the article stems from the need to collect and systemize reliable objective information about living conditions of the population at the local level. A necessary condition for managerial decision-making in economy and social policy is reliable estimation of the population’s living conditions united territorial communities (UTC). The article aims to cover the principles of organization and use of a system of indicators for living conditions of the population at the local level. To achieve this aim, general scientifi c methods are used, namely the method of generalization and the system method. The novelty of the article is the formulation of the principles of systematization of information on living conditions at the local level in the form of a system of indicators and the defi nition the tasks of such a system, as well as data sources for implementation these tasks. Based on Ukrainian approaches, “living conditions” are defi ned as a component of quality of life, which includes three groups of indicators: housing availability, quality characteristics of housing and the level of development and accessibility of social infrastructure. Also, to take into account the European experience of studying the living conditions of the population at the local level, for subjective assessments of satisfaction with life of the local population in the settlement, a particular section is introduced in the system of indicators. The focus of this article is on the subjective component, namely the ability to measure life satisfaction in the community and ways to use such subjective assessments within the system of indicators of living conditions at the local level. Satisfaction with life in the settlement is defi ned as an individual’s assessment of quality of own life according to a criterion chosen in a certain way. Several approaches to measuring life satisfaction in the settlement are introduced: approaches in which satisfaction with life is measured on the basis of one indicator, and approaches in which several indicators are used. If satisfaction with life is measured by one direct question, it is one indicator, but in the case of several statements that the respondent evaluates on a certain scale, each statement is a separate indicator. In the further analysis of the collected data such indicators can be analyzed separately or simultaneously by building a general index. Based on the interpretation of the concept of “living conditions”, this article identifi es three objectives for a system of indicators of living conditions of united territorial communities (UTC): monitoring of living conditions, identifying key problems for UTC and comparing diff erent UTCs on the basis of living conditions of the local population. For the fi rst and third objectives, among the possible sources of information, data from registers are offered, and for the second purpose we off er expert surveys, focus group discussions, open group discussions. The problems of data representation are also discussed in this article. Despite the data being quite fragmented, the format of their presentation should be easy for users (both local authorities and community activists and the media). One possible way to present such data is the format used within methodology of citizen report cards. References: Cherenko, L. М. (Eds.) (2006). Riven zhyttia naselennia Ukrainy [The standard of living of the population of Ukraine]. NAN Ukraine. Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine; State Statistics Committee of Ukraine. Kyiv: Konsultant. Retrieved from https://idss.org.ua/monografi i/riven_juttya_ naselennya%20krainu.pdf [in Ukrainian]. Sotsialni indykatory rivnia zhyttia naselennia Ukrainy. Statystychnyi zbirnyk [Social indicators of living standards of the population of Ukraine. Statistical collection]. (2018). Kyiv: State Statistics Committee of Ukraine [in Ukrainian]. Libanova, Е. М., Gladun, О. М. … & Lisohor, L. S. (2013). Vymiriuvannia yakosti zhyttia v Ukraini. Analitychna dopovid [Measuring the quality of life in Ukraine. Analytical report]. Kyiv [in Ukrainian]. Quality of life in cities. Perception survey in 79 European cities. (2013). Luxembourg: Publications offi ce of the European Union. https://doi.org/10.2776/79403 Urban Europe Statistics On Cities, Towns And Suburbs. (2016). Luxembourg: Publications offi ce of the European Union. https://doi.org/10.2785/91120 The State Of Canada’s Cities And Communities. (2012). Federation of Canadian Municipalities. Retrieved from https://suma.org/img/uploads/documents/FCM%202012%20 State% 20of%20Cities%20and%20Communities.pdf Urban Audit. Methodological Handbook. (2004). Luxembourg: Offi ce for Offi cial Publications of the European Communities. Retrieved from https://ec.europa.eu/eurostat/ramon/ statmanuals/fi les/KS-BD-04-002-EN.pdf Regions at a Glance. (2013). OECD. retrieved from https://www.oecd-ilibrary.org/docserver/ reg_glance-2013-en.pdf?expires=1604570142&id=id&accname=guest&checksum=EA9 1910A605F108551E8EA4E726DE283 Regional Well-being: a user’s guide. (2018). OECD. Retrieved from https://www. oecdregionalwellbeing.org/assets/downloads/Regional-Well-Being-User-Guide.pdf Andreoli, F., & Michelangeli, A. (2015). Welfare measures to assessurban quality of life. Retrieved from http://www.ecineq.org/ecineq_lux15/FILESx2015/CR2/p150.pdf Local quality of life counts. A handbook for a menu of local indicators of sustainable devel opment. (2000). Department of the Environment, Transport and the Regions. London. Retrieved from http://library.uniteddiversity.coop/Measuring_Progress_and_Eco_ Footprinting/ Local%20Quality%20of%20Life%20Counts.pdf Diener, E. (1985). The Satisfaction With Life Scale. Journal of Personality Assesment, 49, 71-75. https://doi.org/10.1207/s15327752jpa4901_13 Khutka, S. V. (2007). Problema vymiriuvannia rivnia sotsialnoi adaptovanosti osobystosti: vyznachennia kliuchovoho indykatora [The problem of measuring the level of social adaptability of the individual: the defi nition of a key indicator]. Naukovi zapysky NaUKMA. Sotsiolohichni nauky — Scientifi c notes of NaUKMA. Sociological sciences, 70, 27-33 [in Ukrainian]. Levinson, А. (2007). Otkrytye gruppovye diskussii kak metod prikladnyh sociologicheskih issledovanij [Open group discussions as a method of applied sociological research]. Vestnik obshhestvennogo mnenija. Dannye. Analiz. Diskussii — Bulletin of public opinion. Data. Analysis. Discussions, 6, 45-54. Retrieved from http://ecsocman.hse.ru/ data/2011/01/14/1214868123/6.PDF [in Russian]. Methodological manual on city statistics. (2017). Luxembourg: Publications Offi ce of the European Union. https://doi.org/10.2785/708009 Citizen report card surveys - A note on the concept and methodology (2004). Social Development Notes. Participation and Civil Engagement, 91. The World Bank. Retrieved from https://openknowledge.worldbank.org/bitstream/handle/10986/11277/286010CRC0SD0 note 09101public1.pdf?sequence=1&isAllowed=y Lakshmisha, A. (2018). Citizen Report Card - A powerful social audit tool. Retrieved from https://www.civilsocietyacademy.org/single-post/citizen-report-card Ogay, М. Yu. (2010). Metodolohiia kartok hromadskoho zvituvannia yak instrument otsiniuvannia yakosti munitsypalnykh posluh [Methodology of public reporting cards as a tool for assessing the quality of municipal services]. Statystyka Ukrainy - Statistics of Ukraine, 2, 14-18. Retrieved from http://194.44.12.92:8080/jspui/bitstream/123456789/ 685/1/14-18_2%272010%2849%29_Ogay.pdf [in Ukrainian].

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.010

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 head0.017
GPT teacher head0.202
Teacher spread0.185 · 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
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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