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Record W4234593029 · doi:10.33137/incite.2.32823

Gracias Mujer

2019· article· en· W4234593029 on OpenAlexvenueno aff
Tamara Valdivia Pariona

Bibliographic record

Venuein cite journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHonourGratitudePersonhoodPhenomenonAcknowledgementGender studiesDignitySociologySacrificePsychoanalysisPsychologyAestheticsHistorySocial psychologyArtPhilosophyEpistemologyLawPolitical science

Abstract

fetched live from OpenAlex

Throughout my life, my relationship to womanhood has been an ever-changing phenomenon. In reflecting on the instances that have come to define this relationship, I wrote “Gracias Mujer,” an homage to the women who have shaped my womanhood and a simultaneous rejection of all that has burdened me. In light of the gendered dynamics within Latino culture, this piece reflects on my complex relationship with my parents and my desire to find healing from personal experiences. Incorporating themes of womanhood, memory, childhood, and family, “Gracias Mujer” is an acknowledgement of my traumas, a love letter to my mother, and a validation of my desires as a Latina woman within an often-confined space. In this poem, without romanticizing them, I try to honour the sacrifices the women and ancestors in my life have had to make, expressing a gratitude for their contribution to my personhood, but also explicitly stating that the trauma that has resulted stops within me.

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0170.005

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 head0.020
GPT teacher head0.331
Teacher spread0.311 · 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
Published2019
Admission routes1
Has abstractyes

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