Bibliographic record
Abstract
Halal Love (and Sex)(2015)Directed by Assad FouladkarHalal Love (and Sex) offers a glimpse into the love lives of three couples: based on real life events, it presents three interwoven stories about the affairs of the heart, as they play out in the culturally liberal yet religious conservative city of Beirut. Three couples, all devout Muslims, display how they are sometimes aided and often hindered by Shari'a law in the way they live and love.Far from the world of Islamic fundamentalism and terrorism that is often the plot line to a popular film about Islam today, Halal Love (and Sex) provides a comedic and heartbreaking view of the laws that surround marriage, relationships, divorce and...well...sex in Islam. The film begins with a school teacher trying to explain how children are conceived to a class of young school children; she explains that a worm comes out of the man and walks over and enters the woman, which then becomes a baby. Needless to say, various irrational explanations are often given to children when adults try to explain the birds and the bees (remember the baby-carrying stork?). Setting the tone for the rest of the film, the viewer soon realizes that some interpretations of religious laws, in this case Islamic Shari'a law, often seem as irrational.In the first story, Awatef and her husband Salim are happily married with two young girls, yet Awatef finds herself physically exhausted from her daily routine and tries to find a way to ward off her loving husband's nightly pursuits of lovemaking. Using the Islamic law which states that a husband is allowed to take four wives to her advantage, Awatef find herself a wife to replace her when her husband's sexual demands are too tiring for her. Although Salim loves his wife dearly and even espouses the Islamic edict that if a man cannot treat his wives equally, only take one wife, Awatef cannot help see the idea of a second wife as a huge boon to her own life; someone with whom to also share the cooking, cleaning and childrearing. What Awatef comes to soon realize in her life is that her husband and children can also come to enjoy having a second wife around, perhaps a little too much.The second story revolves around a young jealous husband, Mokhtar, who keeps divorcing his beautiful wife Batoul during fits of jealous anger. Unfortunately, after claiming to divorce his wife for a third time, he finds himself unable to reconcile with her as they have reached their third divorce and remarriage. …
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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 | 0.000 | 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 | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".