Bibliographic record
Abstract
There's no new land, my friend, noNew sea; for the city will follow you,In the same streets you'll wander endlessly. . . .- "The City" by CP. Cavafy, translated by Lawrence Durrell in JustineAgriculture made the nomads settlers, and trade and other economic opportunities made the settlers immigrants. Vassanji interweaves several such narratives of trade and opportunity diaspora where individuals migrate for commerce and occupation. These willing immigrants travel across continents carrying the memory of their land left behind, and make an attempt to reconstruct it with social and symbolic capital. Vassanji’s novel, No New Land is one such narrative relating the immigrant’s odyssey where the emotional transition spans longer than the physical passage. It is the tale of the sixty-nine Rosecliffe Park located in imaginary Don Mills in the city of Toronto, and its heterogenous immigrants representing different ethnicities. However, the physical structure of Sixty-nine Rosecliffe Park is a construction of every resident’s’ cultural memory and social capital. The edifice and its environment are an ecosystem created by its inhabitants in order to promote multicultural sustenance. The proposed essay will make an attempt to examine the environmental and cultural conflicts the Asian and African immigrants confront in Canada, followed by the triumph of their socio-cultural mobility. I intend to highlight the efforts of immigrants in reconstructing a similar land which lies in the past using collective cultural memory, and their ability to find a connecting line between both their homeland and their foster land.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.018 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".