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Record W4291901065 · doi:10.51644/wxwm9625

Shaking the Leaves of Identity

2022· article· en· W4291901065 on OpenAlexaff
Rosalyn Kantlaht’ant Elm, Janaki Bandara

Bibliographic record

VenueConsensus · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPentecostalism and Christianity Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPersonhoodIndigenousClanIdentity (music)Human sexualityOriginal sinSociologyPhilosophyHistoryAnthropologyLiteratureAestheticsGender studiesTheologyArtEpistemologyEcologyBiology

Abstract

fetched live from OpenAlex

This article seeks to present a study of gender and sexuality based on an Indigenous and theologically interpreted understanding of ourselves, wonderfully made by God, who formed our inward parts and knit us together in our mother’s wombs. If we understand personhood in general and gender in particular to be a matter of lived experience rather than merely a matter of physicality, biology, and physiology, then our hearts and our spirits can be open to experiencing all people as Creator made them rather than through very limiting, merely mortal definitions. This article accesses the lived experience of Anglican Archdeacon Venerable Rosalyn Kantlaht’ant Elm, born of the Oneida Nation, Bear Clan, whose name Kantlaht’ant means “One who Shakes the Leaves,” and who is identified by the Haudenosaunee term laksá. The concept of the Resurrection Body from Pauline scripture and a traditional hermeneutical lens are used to affirm that all that Creator makes has been, is, and always shall be glorious.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.053
Scholarly communication0.0070.009
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.053
GPT teacher head0.245
Teacher spread0.192 · 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
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 routes1
Has abstractyes

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