Bibliographic record
Abstract
Memories establish a connection between a collective and individual past, between origins, heritage, and history. Those who have left their places of birth to make homes elsewhere are familiar with the question, "Where do you come from?" and respond in innumerable well-rehearsed ways. Diasporas construct racialized, sexualized, gendered, and oppositional subjectivities and shape the cosmopolitan intellectual commitment of scholars. The diasporic individual often has a double consciousness, a privileged knowledge and perspective that is consonant with postmodernity and globalization.The essays in this volume reflect on the movements of people and cultures in the present day, when physical, social, and mental borders and boundaries are being challenged and sometimes successfully dismantled. The contributors - from a variety of disciplinary perspectives - discuss the diasporic experiences of ethnic and racial groups living in Canada from their perspective, including the experiences of South Asians, Iranians, West Indians, Chinese, and Eritreans. Diaspora, Memory, and Identity is an exciting and innovative collection of essays that examines the nuanced development of theories of Diaspora, subjectivity, double-consciousness, gender and class experiences, and the nature of home
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 | 0.005 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".