Bibliographic record
Abstract
本文為筆者受客家委員會客家研究發展中心委託撰寫之《北美洲客家研究計畫》的田野紀錄，此計畫以建置海外客家研究之基礎資料為研究主軸。如標題所示，重點針對於來自世界各地的客家族群移民北美洲的歷史，以及客家族群在美國各大城市所聚集會館、同鄉會之研究。不過基於研究規模的考量，現以最主要的華埠城市，如美國舊金山、洛杉磯、紐約與西雅圖市，以及加拿大維多利亞市作為研究對象，田野紀要將提供未來從事相關研究專家學者參考。2016年間，研究團隊兩度前往美國、加拿大，以現存客家團體、墓園與檔案館作為研究對象，過程中所蒐集文獻資料將協助研究者能更精確尋找客家移民與檔案，藉此重構消失的北美洲客家移民史。This is a fieldwork report about a project name “Hakka Research Project of North America” sponsored by Taiwan Hakka Culture Development Center of the Hakka Affairs Council, mainly constructing a basic data for the study of overseas Hakka. The current study focuses on the history of Hakka immigrants from all over the world in North America and studies of Hakka ethnic associations established in major cities, along with early study of North America Hakka immigration within some of the most important Chinatown cities. In 2016, our research team traveled to the United States and Canada twice separately, studying the remaining Hakka organizations and archives, helping researchers more accurately finding historical data about Hakka migrants and to reconstruct the history of North America Hakka immigration.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".