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Record W3084420571 · doi:10.18280/ijsdp.150608

Sustainable Management of Productive Cultural Landscapes: The Pascual Harriague Wineries in Salto as a Case Study

2020· article· en· W3084420571 on OpenAlex
Ander de la Fuente Arana, U. Llano Castresana

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanism, Landscape, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEnvironmental resource managementEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

This article proposes guidelines for the creative management of productive cultural landscapes. These guidelines are briefly illustrated with reference to a case study: the productive cultural landscape of wine and vineyards in the riverside city of Salto, Uruguay, during the last years of the 19th century. The proposed guidelines follow the order and approaches of the links in the Landscape Value Chain. These steps are applied to the landscape from a triple approach, as memory, image and socio-system. Thus, the identification of traces and narratives of memory, elements of image and poles of opportunity of the socio-system is proposed. Each element is valued, considering its potential for re-signification and its cost. An intervention is also proposed, based on reversibility and humility. And, at all times, a process of dissemination or accountability and socialization or social dialogue is maintained. In conclusion, the recovery of a landscape must be understood as something that implies re-signifying its memory (activating its traces with narratives), the restoration of its image (giving it continuity) and restoring its social system (reactivating the socioeconomic dynamics based on the feeling of belonging), through an adequate social participation and a required subjective, non-positivistic approach to the processes, to achieve our objective: the recovery of the character of a productive cultural landscape to encourage the entrepreneurship of its inhabitants.

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.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.304
Teacher spread0.279 · 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