Bibliographic record
Abstract
Remake, reboot, sequel, prequel sont des termes qui sont employés de manière récurrente pour désigner les phénomènes de sérialité qu’impliquent notamment les franchises hollywoodiennes à succès. Dans le cadre de cet article, nous nous concentrons sur le Star Trek de J.J. Abrams, sorti en 2009, ainsi que sa suite Star Trek Into Darkness, sortie en 2013. Nous mettrons en exergue en quoi le film de J.J. Abrams nous parait être un cas unique au moment de sa sortie en 2009 dans la mesure où il peut s’interpréter à la fois comme reboot, préquel, suite et comporte en son sein des éléments de remake. D’un point de vue narratif et esthétique, Star Trek et sa suite se révèlent être d’autant plus pertinent à étudier sous cet angle que la conscience de l’auteur de cette particularité pour ces films apparait limpide. En résulte une mise en scène qui joue sur l’intertextualité, notamment par le biais de figures de style, mettant en exergue le caractère singulier de l’oeuvre d’un point de vue de l’étude sérielle.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".