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Record W7002285134

The Monster in Her Blood

2023· dissertation· en· W7002285134 on OpenAlexaboutno aff

Bibliographic record

VenueSkemman · 2023
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMonsterRidiculousPoint (geometry)Perspective (graphical)
DOInot available

Abstract

fetched live from OpenAlex

The following MA thesis contains a novella of approximately 20,000 words with an accompanying expositional piece of approximately 7,000 words.It is best defined as a contemporary American Gothic.Set in a small Northern village in the United States on the border of Canada, we see the humble beginnings of one man and subsequently the parallel life of his daughter.Using the elements of light and dark, super-imposed with the four seasons of the year to represent the Gothic tropes of the sublime and the supernatural, the reader will witness the evolution and at times devolution of both characters throughout the years of their lives.This novella can best be described as an American Gothic, in which the environment itself acts as a component of common Gothic tropes.In the summer, the main characters and the small village's inhabitants enjoy the fruits of the lush easily farmable lands and use its expansive lake for recreation and relaxation.When winter and blustery weather arrive, we see its inhabitants forced inside their homes, placing them into small dark places, where boredom often leads to the common American escapism of alcoholism and drug addiction leading to the existence of domestic violence.This novella's main characters were inspired from my first year of literature, when I learned Lacan's theories of the mother and the father, and Jung's Sage and Great Mother archetypes.There is a strong focus on the existence of the dark side of the mind and human psyche that exist in the mundane aspects of American life, and consequently the bad decisions that define humanity.The reader will experience the peaks and valleys of the character's simple lives, and in the end their inevitable survival.Intertwined with shadows, monsters and things that go bump in the night, I hope you enjoy this contemporary American Gothic.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.017
GPT teacher head0.293
Teacher spread0.276 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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