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Record W7162187411 · doi:10.59236/emro.v25i2a7935

Drunk on Too Much Life

2023· article· W7162187411 on OpenAlexaboutno aff
Bryan J. Sajecki

Bibliographic record

VenueEducational Media Reviews Online · 2023
Typearticle
Language
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)NarrativeTone (literature)Mental illnessStigma (botany)GazeBlamePersonal narrative

Abstract

fetched live from OpenAlex

Distributed by New Day Films, 350 North Water Street Unit 1-12, Newburgh, NY 12550; 888-367-9154Produced by Michelle Melles and Pedro Orrego, Parallel Vision PicturesDirected by Michelle Melles2021, Streaming, 77 mins Psychosis is terrifying to imagine; hearing voices, seeing visions, believing self-created narratives that are anything but true. Within the sphere of mental illness, it is incredibly difficult to treat, usually combining a cocktail of medications with an assortment of different therapies. Beyond that, the stigma surrounding the diagnosis and condition can be suffocating and altogether exclusionary and harmful. In a general sense, unless a person has been in the shoes of another, they can only scratch the surface of understanding how something feels. And for the affected person, they are more than likely desperate to make meaning of it themselves. What does it all mean? Is this real? Will it go away? Drunk on Too Much Life is a documentary that seeks to reimagine the definition of madness and the understanding of mental illness. It is incredibly unique in that the director, Michelle Melles, has a personal connection to the project, as the film’s main player is her daughter, Corinna. At the onset, the tone is heavy and oppressive, as the viewer watches an emerging adult trapped in her own fears of spiraling into an episode, shaking while she sleeps amidst a catatonic plunge. That fear is very real for her because she has been there before. It is like a dark passenger that creepily follows a few paces behind, whispering when she gets a bit too far for its liking. Despite the whispers, Corinna has a plan; she wants to understand her condition and figure out how to harness it. Perhaps it can be leveraged like a superpower, or a gift? And going further, who is going to stop her from trying? Like a myriad of films before it, the subject of the limitations of psychotropics as a magic bullet is discussed. This conversation occurs throughout, as Corinna meets several supporters that become companions on the journey. With the help of her family, she embraces holistic approaches to treating her condition, such as poetry, music, and art. These provide a necessary catharsis, as she uses the mediums to speak the words she cannot find to describe her feelings. The viewer can see the light in her eyes as she sings (even if she is off key) and hear the power in her voice when she recites a prose poem. Ultimately, she wants to control her “superpowers” so she can help her peers in this battle, demonstrating how pure her heart is. The film smartly uses animated collages to transition between scenes, often including one of Corinna’s songs or stanzas to continue telling the story even in a break of sorts. It also serves as a much needed aesthetic to break up the heavy undertones of the subject matter. Family pictures are also used to enhance the story, showing the chronology of Corinna’s life through her descent into madness. Additionally, interviews with psychologists and with those who also live with the dark passenger provide a sense of hope and understanding. Their contextual expertise helps to shed light on the belief that this condition can be harnessed because they have done it or assisted others in the task. Drunk on Too Much Life is a poignant documentary that provides a distinct point of view regarding psychology and mental illness that others before it have failed to do. It destroys any sense of stigma and any viewer is surely better for it. This film will be a strong addition to any academic library, especially one with a strong health science, mental health, or social work background. Awards:Official Selection, Social Change Film Festival (Chicago, New York City, Los Angeles), 2022; Official Selection, Mental Filmness Festival (Chicago), 2022; Official Selection, Rendezvous With Madness Festival, Closing Night Film, Toronto, 2021; Quarter Finalist, ReelAbilities Film Festival, New York, 2022; The Gold Medal, The Creative School, Toronto Metropolitan University, 2021; Merit of Awareness (Honorable Mention) - Awareness Film Festival 2022

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.196
Threshold uncertainty score0.656

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1960.043

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 head0.290
GPT teacher head0.523
Teacher spread0.233 · 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
GenreOther

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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