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Record W4307101849 · doi:10.5539/jsd.v15n6p24

Territorial Development at the Crossroads of Attractiveness and Sustainability

2022· article· en· W4307101849 on OpenAlexvenueno aff
Hanene Ben Ouada Jamoussi, Salma Mhamed Hichri, Peter Nijkamp, Walid Keraani

Bibliographic record

VenueJournal of Sustainable Development · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsnot available
Fundersnot available
KeywordsAttractivenessSustainabilityTypologySustainable developmentRanking (information retrieval)Proxy (statistics)Regional scienceOrder (exchange)Economic geographyHomogeneousGeographyEconomicsPolitical scienceEcologyComputer science

Abstract

fetched live from OpenAlex

An abundant literature in spatial planning, economic geography and regional science has focused on territorial attractiveness. However, most literature does not sufficiently integrate recent research challenges induced by sustainable development. The latter issue is likely to modify profoundly the locational determinants of economic activities and the mechanisms that explain the ability of territories to attract economic activities. Consequently, a novel approach articulating the necessity of integrating the concept of sustainable development and territorial attractiveness is pertinent. The purpose of this study is to show to what extent an evidence-based analysis of sustainable development goals affects the classification of countries according to their level of development and their potential to move to a higher ranking of their performance. On the basis of panel data on 52 countries, monitored over the last ten years, and through the explicit consideration of "proxy" variables of sustainability, attractiveness, and economic growth associated with measurable indicators, the paper seeks to assess the main basic trends, to develop a typology according to the main new strategic orientation, and to analyse rank order changes in different homogeneous groups of countries. The results confirm the idea of a general two-dimensional and dichotomic trend towards (or against) sustainability and attractiveness and employment prospects. Our study confirms the widening divide between countries in terms of their socio-economic and environmental policies.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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
Published2022
Admission routes1
Has abstractyes

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