Bibliographic record
Abstract
This article argues that the property television programme, Love It or List It (2008–), employs conventions from the classic screwball comedy to both consolidate its position within the lucrative realty TV market – especially in response to the recent (2008) recession – and negotiate modern gender dynamics within the home. Its Depression-era (1930s) financial and aesthetic resonances are not incidental. And, as with much contemporary culture, this modern iteration of the screwball comedy is not discretely contained by medium or genre of influence: Love It or List It also borrows flourishes from documentary, tabloid TV, melodrama and the gothic novel. In keeping with its reference to a kind of baseball pitching style that is difficult for hitters to anticipate, the screwball’s tendency to suddenly switch course has been identified as its central means for engaging in cultural critique. Love It or List It as an exemplar of reality TV’s recombinant style is still very much like its cinematic predecessor: it has the adeptness to say many things to many audiences. This article makes no claims for Love It or List It’s progressive politics; rather, as with some classic screwball comedies, it explores the possibility that equivocating, shifting course or otherwise abandoning narrative logic register a profound ambivalence about marriage, coupledom and the family home as sacrosanct loci of modern life.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".