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Record W7126359214

Shifting Ground - Muuttuva maa : Volcana Arctica 2022-2023:wool, mixed media textiles and charcoal on wood / villa, tekstiilit ja hiili puulle

2024· article· en· W7126359214 on OpenAlexaboutno aff
Fabiola; id_orcid 0000-0001-6571-5427 Hernandez Cervantes

Bibliographic record

VenueLaCRIS (University of Lapland) · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeExhibitionResource (disambiguation)Scale (ratio)Global warmingProcess (computing)Charcoal
DOInot available

Abstract

fetched live from OpenAlex

The exhibition ‘Shifting Ground’ is envisioned as a platform for transnational creative encounters with the everyday experience of climate change in rural and remote communities of Lapland and northern Canada. ‘Shifting Ground’ aims to contribute new artistic perspectives of Northern communities, peoples, and cultural contexts whose orientations in the global community are fundamentally shifting as a result of climate change. What is the visual language of resource extraction and climate change? How can artworks shift attention to energy in place, represent local realities and figuring futures? How can we use artistic research[1]creation to disrupt the scale of our climactic imaginaries, bringing climate change into view as both an abstract, ‘system-wide’ and visceral, ‘here-and-now’ process that reflect northern experiences? In many ways, artists living and working in Northern ecologies – where the markers of climate change grow ever[1]more salient, and where the rate of warming far exceeds that of more southerly regions – are uniquely positioned to respond to such questions, and to consider the adaptations, challenges, and future possibilities that emanate from them. Shifting Ground – Muuttuva maa invites proposals from artists living in and working on issues of import to Northern ecologies, and which consider climate change through such lenses as: Extraction, consumption, commodification Technologies of adaptation Infrastructure and the built environment Site-specific, collaborative, or context-sensitive pedagogies Water security, habitat loss, or environmental justice Mapping or counter-cartography

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.159
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.001

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 head0.278
Teacher spread0.253 · 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
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
Published2024
Admission routes1
Has abstractyes

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