“I Long For My Mother’s Bread”: Poetry as Integrative, Historical Practice in the Palestinian Context
Bibliographic record
Abstract
This paper is an adaption of a longer investigation of the relationship between politics and poetry in the Palestinian context, focusing on the work of Mahmoud Darwish. For this selection, I have adapted the sections pertaining to the efficacy of poetry in the context of historical events–specifically the traumatic history of the Palestinians. It is my argument that artistic practices like poetry act primarily as a means of narrative creation that skillfully integrate the experiences of the poet and thus negotiate the experiences of the listeners in order to create new meaning. This dialogue between audience and poet creates a persuasive and novel movement within the conceptual field; thinking about something in terms of something else (metaphor). This has the effect of making the poet an intractable source of historical meaning. The questions of the past, a dizzying array of dissonant occurrences, fractured experiences, and selected memory, find cogency within the poetic form. This artistic formation only gains this cogency through a precise system of cognitive faculties, which are shared by both poet and audience. The poetry of Mahmoud Darwish acts as a means of understanding history in the context of the present; creating an integrated narrative-history, which has important implications on experience, implicating present action through a ‘reading’ of the past.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".