Bibliographic record
Abstract
The network model has become a powerful tool for shaping an imaginary of social organization and communication in contemporary life.As individuals become increasingly connected via communication technologies, we also face a heightened sense of alienation and disorientation.In this thesis I argue that David Lynch and Mark Frost's eighteen-episode television series Twin Peaks: The Return crafts a roadmap though this disorientation.By drawing attention to historical events represented in the series, namely the Trinity nuclear test, I will show the ways in which the series is interested in how specific aspects of American history created the foundation for contemporary notions of communication breakdown.I connect this historical framework to a textual analysis of The Return to argue that the series' aesthetic engagement with intense affects, namely anxiety, is connected to how it represents networked modes of communication.networks and devices have fundamentally changed the ways in which we communicate with one another.Twin Peaks: The Return (David Lynch and Mark Frost, 2017) is a television series that is obsessed with how we communicate.It maps the complicated and interconnected networks of communication across geographical space and then through time.In representing these networks, narratively and formally, The Return reveals a concern with how the past, the pasts of characters and of American history, effects the present.The Return is the eighteen-part continuation of the series Twin Peaks, which aired on ABC (American Broadcasting Company) for two seasons (a total of thirty episodes) between 1990-1991.Both Twin Peaks and The Return were created by American filmmaker, writer and multi-media artist
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 | 0.001 | 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 | 0.005 | 0.018 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".