MétaCan
Menu
Back to cohort
Record W2804857238 · doi:10.12835/ve2017.2-0088

Culture Sensitive Participatory Art as Visual Ethnography in the North

2017· article· en· W2804857238 on OpenAlexaboutno aff
Timo Jokela

Bibliographic record

VenueVisual Ethnography · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyDialogical selfIndigenousVisual anthropologyCitizen journalismSociologyVisual artsVisual cultureMetisArcticAnthropologyAestheticsMedia studiesArtPsychologyPolitical scienceSocial psychologyComputer scienceEcology

Abstract

fetched live from OpenAlex

The article discusses how community-based environmentalart has used to help Northern and Arctic peoples to communicate their own visual and eco-social environmental culture by analyzing it from the inside. Artistic activity draws its content from the northern places, while combining traditional, non-artistic working methods and Sami indigenous practices with dialogical and relational contemporary art. Often the processes are parallel and overlapping with the methods of visual ethnography. The article presents the premises, processes, and execution of two artistic projects: Kirkkokuusikko memorial (2009) in Lapland, Finland as an example of an artist personal effort, and selected examples of the result of long term collaboratively and multidisciplinary winter art development (2003-2016) in Northern Scandinavia and Russia. These projects shed light on the interaction between the environmental art practises, visual ethnography and decolonizing effect of community based participatory approaches in the North.

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)0.018
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.990
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0120.049
Scholarly communication0.0100.008
Open science0.0020.014
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.102
GPT teacher head0.471
Teacher spread0.369 · 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 designQualitative
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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueVisual EthnographySame topicIndigenous Studies and EcologyFrench-language works237,207