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Record W4416565024 · doi:10.52783/tangence.22

Heritage Conservation and Sustainable Development: A Legal Perspective

2025· article· W4416565024 on OpenAlexvenueno aff

Bibliographic record

VenueTangence · 2025
Typearticle
Language
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsCultural heritageCultural heritage managementSafeguardingIndustrial heritageUrbanizationHarmony (color)Urban planningVitality

Abstract

fetched live from OpenAlex

Preserving heritage amid rapid urbanization is pivotal to sustainable development. Heritage sites reflect cultural narratives, but urban expansion often results in their neglect or demolition. Striking a balance between development and safeguarding cultural heritage poses a complex challenge for policymakers and urban planners. The paper explores the intersection between cultural pasts and urban histories relating to the gentrification, heritage and cities with forces of globalisation and legal framework. The paper will further examine achieving harmony between progress and preservation of culture which necessitates a holistic approach that values both the economic vitality of cities and their cultural heritage and the challenges of urban development. Drawing insights from cultural pasts becomes crucial for crafting sustainable, inclusive, and culturally vibrant urban futures. The researchers plan to analyse the laws relating to protection of cultural heritage in India and some select countries. The researchers shall analyse the strategies employed in India and compare the best practices prevalent in other countries. To summarise the researchers shall: Compare the laws relating to preservation of cultural pasts and urban histories. To look into the harmonisation of Heritage preservation and sustainable development through effective legal framework .

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.041
GPT teacher head0.248
Teacher spread0.207 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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