MétaCan
Menu
Back to cohort
Record W2580322694 · doi:10.31165/nk.2016.96.486

Algorithmic love: “Quit playin’ games with my <3”

2016· article· en· W2580322694 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNetworking Knowledge Journal of the MeCCSA Postgraduate Network · 2016
Typearticle
Languageen
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsConcordia University
Fundersnot available
KeywordsSubject (documents)MythologyObject (grammar)Sign (mathematics)MeditationTheme (computing)Ideal (ethics)Computer scienceEpistemologyFunction (biology)AestheticsSociologyCognitive sciencePsychologyArtificial intelligencePhilosophyArtLiteratureMathematicsWorld Wide Web

Abstract

fetched live from OpenAlex

Some of the rich history of the <3 is laced with myths and monsters, and reveals this particular cipher is anything but a trivial emoticon: rather, its ambiguous affective weight makes it an ideal interface for the ineffable. This conceptual essay is an exploration through a different approach to the traditional visual essay. Here, the author-composed photo-collages function as a meditation on a theme by pondering and theorizing along with the text, ideas of the heart emoticon in the fractal matrix of sign types, with some of the multiple possibilities and implications associated with its use by both individuals and corporations. Paralleling the subject/object relations figured forth through the Medusa myth, with the idea that not knowing about the algorithmic influences on the <3 of intimate digital messaging may serve to turn the subject into an object. This paper thus calls for algorithmic literacies, broadly conceived as agility in critically discerning how decision-making is presented to the individual in matters of the <3.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0050.002
Research integrity0.0000.001
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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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