Bibliographic record
Abstract
Remembering storiesIn the midst of stories A middle daughter storyIn this in-between place, of living then and now, now and then, and straining to see what lies ahead, exists a space where I am searching for the story of self.It is as if I am back in the old family Buick, stuck in the middle with my sisters, vudiand shoti, on either side.Pitha determined in his driving to get there faster than the last time.Matha's distant gaze overlooking lane dividers, highway, and mountains, reaching memories that carry her away.Soft breath released and shaped between faithful lips couples hymns floating out of the tape cassette, her only existence in this car.I push myself up on the palms of my hands, craning my neck left or right to catch glimpses of the world whirling by.Fast and furious images become blurs of colours, making me dizzy.I grasp Pitha's and Matha's seats and pull myself forward to look out the front window.We never seem to get there and the seatbelt resists and resents my curiosity, digging deep into my stomach.I maintain this uncomfortable stretch hoping to see something new.That is until Pitha or Matha or both scold me for not sitting in my seat.Flopping back, I look for stories hidden in the folds and cracks of the burgundy velour and vinyl interior.Listening.Hearing only Matha's murmuring and the motor running.Quietly, carefully, I turn around on my piece of the backseat, lay my forearms upon the ledge, and place my chin where hands overlap.Watching the road we have just traveled, the sights just seen, the now moments suddenly becoming the past, hold me still.And still hold me. Write in the MiddleNestling into a seductive space that invites remembering, reflecting, and writing, I find comfort in the gentle rocking that takes me back to the past, eases into the present, and forth to the future, only to repeat itself.As
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.059 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".