Bibliographic record
Abstract
I have been away from Pakistan for almost 20 years now and only have been able to go back four times. I have daydreamed of reuniting with my mother since I stepped into the airport to leave her behind. I experience the constant longing to return to my mother, to home, when I am watching a sunset; from the sudden whiff of jasmine flowers on the footpath, from the smell of ittar I wear; while making biryani from shaan spices packed in Pakistan; on Eids, on birthdays, on my leaving home anniversary date and month; on labels on towels reading made in Pakistan in our local supermarket shelves and in the pages of Urdu novels and poetry; from the lyrics of songs; from twirling between my fingers the locket my mother gave me to ward off evil; when I raise my hands to pray at the end of the fajr prayer; when I get sick and want my mother to nurse me back to health – when living. I have a powerful unshakeable spiritual bond with my mother. The dream I share in this piece, as interpreted by my mother, is a desire to return home and the testimony of my love for her.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.025 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".