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Record W4293078411 · doi:10.32920/19519726

Sentiment Analysis: The Water Crisis

2022· preprint· en· W4293078411 on OpenAlexaffabout
Makenzie Smeriglio

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIndigenousNarrativePoliticsColonialismPolitical scienceEmpathyMythologyPerspective (graphical)Political economySociologyHistoryLawSocial psychologyPsychologyArtLiteratureEcology

Abstract

fetched live from OpenAlex

This research examines the issue of the water crisis from an Indigenous Feminisms perspective. The First Nations Water Crisis is the issue of long-term water advisors that Indigenous communities have had and are currently still experiencing. It is a complex issue stemming from settler colonialism, and the broader Canadian public does not understand it well. This research examines public sentiments in the comment sections of news stories about First Nations and the water crisis. This is to identify settler-colonial mythologies about Indigenous peoples and offer counter-narratives. Clean water is a basic necessity and should be offered to everyone. By addressing hateful socio-political imaginaries and offering counter-narratives, we can work towards changing people's opinions from apathy to empathy. We can also work towards making real positive changes to the First Nations Water Crisis.

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)0.003
metaresearch head score (Gemma)0.009
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.067
GPT teacher head0.277
Teacher spread0.210 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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