<i>Breaking Bad</i> and <i>Better Call Saul</i>: Struggling and Living in Liquid Times
Bibliographic record
Abstract
AMC’s TV series Breaking Bad and Better Call Saul both feature protagonists who can be seen as victims of institutions that do not appreciate their talents and abilities. Walter White in Breaking Bad, who once won a Nobel Prize in chemistry, is an under-appreciated and underpaid high school chemistry teacher who must work a second job to support his family. Jimmy McGill, a con artist–turned–lawyer who will eventually change his identity to Saul Goodman in Better Call Saul discovers that because of his earlier criminal exploits and non-traditional legal education, he will never be fully accepted within Albuquerque’s legal community. These series exemplify several core concepts from Zygmunt Bauman and Martin Shuster’s works, including liquid modernity and late capitalism, the loss of normative authority and deinstitutionalization, the process of individuation and identity formation, and the centrality of family in living and struggling in liquid times.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".