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Record W2804897530 · doi:10.5194/ica-proc-1-42-2018

Seeing the unseen: an Indigenous heritage’s mapping project

2018· article· en· W2804897530 on OpenAlexfundaboutno aff
Justine Gagnon

Bibliographic record

VenueProceedings of the ICA · 2018
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousGeographyHistoryEnvironmental ethicsBiologyEcologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract. Based on an ongoing qualitative and collaborative research project led in partnership with the Innu community of Pessamit, this paper brings into focus some specific issues regarding memories recollection and representation in a context of deterritorialization. The Innu First Nation has a specific historical and political context related to resources exploitation. Since their traditional lands have been the site of several large-scale hydroelectric projects, they have been intimately – and to a large extent, forcibly – involved in the economic transformation of Quebec since the 1950s. It should be noted, however, that their ancestral occupation has never been formerly recognized by the federal and provincial governments, a political and legal context partly responsible for the material and cultural losses they had to deal with. Through interviews we have conducted with the elders that travelled the rivers before the floods, we tried to rebuild, in some way, the cultural heritage embedded in those submerged lands. We used different cartographic tools and materials in a way to support and trigger the personal narratives the elders were remembering and sharing. This cultural mapping process revealed three main issues I would like to focus on. First, as the cartographic representations were getting closer to the landscapes the elders perceived and experimented as kids and young adults, the localization of significant places and the creation of personal narratives became easier and fluid. Secondly, we found, through that inquiry, how important an enhanced visibility of innu’s flooded heritage can be on a political level. Finally, we came to the conclusion that mapping should be considered more as a conversation than a visual representation only.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.334

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 science0.0010.000
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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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.

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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the ICASame topicMemory, Trauma, and CommemorationFrench-language works237,207