Bibliographic record
Abstract
Throughout her entire life, Elizabeth Bishop constantly reveals her preferences for writing poems full of images and motifs of water. Bishop’s poems often suggest elusive meanings like the dual properties of water which shows the difference between the surface and depth at the same time. Particularly, it is worthwhile to note Bishop’s third book of poems entitled Questions of Travel. This book includes a number of poems about recognizable water images from Nova Scotia to Brazil where the poet spent precious periods in her life. Images of water in a lot of her poems set in North America are described as dry and barren landscapes due to her sense of homelessness derived from the loss of her parents in her early childhood. This is best exemplified in her expression of “the water doesn’t wet anything.” However, it is important that Bishop’s maternal desire is latent under the surface of her poems on the loss of maternity. Her maternal imagination linked to the water images is most manifested in her poems on the “Brazil” section of Questions of Travel. Moreover, a series of poems with images of water devoid of fluidity and maternity set in Nova Scotia allude to Bishop’s latent maternity. Bishop’s water images lurking in maternal desire act as a source to dissolve the dichotomous thinking originated from Western Chauvinism.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".