Abu Hasan's Meager Palestinian Repast: Memories, Past and Present
Bibliographic record
Abstract
What started out as a brief recounting of the June 21, 2021, noon meal for two friends on our back porch evoked myriad memories, past and present, and sprouted too many legs, twists, and turns in the Shahrazad style.\nBetween 1950 and 1959 Im (mother of) Hasan (nicknamed after her first-born) delivered milk on her donkey. She would leave the Palestinian village of Beit Safa in the wee hours of the morning to deliver goat milk to some 20 Palestinian families scattered in Occupied West Jerusalem neighborhoods. Dressed in the traditional tatreezed (embroidered) Palestinian Thowb and thin linen head scarf, and riding her donkey, she cut a regal figure. The large canisters of milk dwarfed her petite stature. My twin brother and I quickly learned that when her donkey pulled his ears towards the back of his head, he was ready to kick ass.\nSometime in 1955 Abu (father) Hasan, Im Hasan’s husband, a stone mason and jack of all trades, was employed to shore up a column on the first-floor balcony at the back of our West Jerusalem, Upper Baqa’a house. During the ten days it took to finish the project, Abu Hasan’s demeanor, humility, kindness, and artistry left an indelible impact on my life. My title, Memories, Past and Present:Abu Hasan’s Meager Palestinian Repast, is a flashback and a 2021 reenactment of the partaking of his meager meals in my adopted country – 10,982 kilometers to the west.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".