REFERENCE: The Arab American Experience in the United States and Canada: A Classified, Annotated Bibliography
Bibliographic record
Abstract
REFERENCE American Experience in the United States and Canada: A Classified, Annotated Bibliography, by Michael W. Suleiman. Ann Arbor, MI: Pierian Press, 2006. xix + 575 pages. Author index to p. 594. Periodicals index to p.601. Country index to p. 604. $129. Reviewed by Paula Hajar In 1989 several dozen scholars from around the world converged on Oxford University for six days to present and debate their research on the Lebanese Diaspora worldwide. Many giants of the field had come: Albert Hourani, Charles Issawi, Afif Tannous, Samir Khalaf, Fuad Khuri, Barbara Aswad, Alexa Naff and others, including a handful like me who, as neophytes, were there simply to listen. In attendance also was Michael Suleiman, who had just recently agreed to be the specialist reader for my qualifying paper on the honor code among Lebanese immigrants. An authority on sources, Suleiman had the reputation of being able to tell where a research work was thin and then suggest a dozen or so essays that would make it stronger. By the time of that conference, he had been working on this bibliography for ten years. This book recalls some of the liveliness of that academic soiree at Oxford. Gathered onto its 600 pages and divided into 23 chapters are the works of over two thousand authors, culled, often painstakingly, from over 500 sources. Entries date from the 1840s and continue through 2005, and cover chapters on emigration and immigration; assimilation; marriage and family; health, aging and counseling, socioeconomic status and professions; citizenship; the political process; and education. works cited are primarily in English and Arabic, with a relative few in French. For anyone who has ever labored to track down detailed evidence of the presence of Arabs in the United States and Canada, the book is a godsend. As with any reference material, the power is in the organization. more successful chapters are those in which the entries were sorted into further categories or sub-topics. Thus Biographies and Autobiographies is organized by subject, The Religious Context is divided by sect, the arts chapter is divided by type of art, and Regional Studies is divided, naturally, by state. In the chapter Videos, Films and Web Sites, websites are sorted by the type of institution that they serve. In most chapters, however, the entries are sorted simply alphabetically by author or source. Thus, in the chapters on Women and Gender Studies, Arab American Organizations, and Life in North America one must already know the author one is looking for in order to find anything quickly. Because of the alphabetical organization, one risks missing the historical sweep of the research. …
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.022 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 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".