MétaCan
Menu
Back to cohort
Record W4301521578

Gazimestan and Velika Hoča as potentially protected cultural landscapes in the region of Kosovo and Metohija

2017· article· en· W4301521578 on OpenAlexaboutno aff
Ivanović Miodrag R.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Development and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceGeographyEnvironmental protection
DOInot available

Abstract

fetched live from OpenAlex

The fact that Kosovo and Metohija is rich with archeological remains of numerous and different cultures flourishing and developing within, also numerous medieval monasteries, natural and cultural potentials , history and tradition, point to the possibility that this region could become attractive in future for the tourism and cultural tourism needs. This hypothesis is proved in practice by tourist super powers in Europe and the world, Italy, France, Russia, the USA, Canada, which today levy immense income from cultural tourism, whose constitutive part comprises Cultural landscapes as well. Two such subject areas in Kosovo and Metohija - Gazimestan and Hoča are chosen for the study; by a detailed analysis a conclusion will be drawn whether these areas have potentials to be nominated for the World cultural list as Cultural landscapes in Kosovo and Metohija. The research is multidisciplinary; this paper presents an initial study of cultural landscapes in this region and examines possibility of its culture and tourist presentation. A well organized, conceived and timely placement of cultural landscapes opens a new segment in the cultural tourism offer. This research will prove the importance of promoting cultural landscape and its revival through cultural heritage, as well as its incorporating into modern tourist offer.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.273
GPT teacher head0.477
Teacher spread0.204 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicRegional Development and Management StudiesFrench-language works237,207