Bibliographic record
Abstract
Introduction In May 2012 the oldest Sikh Temple in Victoria, British Columbia celebrated its hundredth year, a testimony to the history of Punjabi immigration to Canada. The Sikh community today is one of the largest and most deeply rooted ethnic communities in Canada. This chapter reviews the literature on the integration of the Punjabi/Sikh community in Canada. In the review of literature the authors have relied on academic books and book chapters, journal articles, newspaper reports and where possible official government data. In a few cases, data cames from findings of research undertaken by reputed and well-established community organizations. Academic research and statistical data in Canada focused on ethnic groups collapse the Punjabi/Sikh community under the heading ‘South Asians’ that includes persons who can trace their origins to India, Pakistan, Bangladesh and Nepal. In doing so, much information about the unique features of the Punjabi/Sikh (and other communities) is lost. This chapter tries not to utilize such data as the category ‘South Asian’ is extremely diverse and could overwhelm the focus on Punjabis/Sikhs that this book strives to achieve. The discussion of the integration of the Punjabi/Sikh community in Canada works within the limitations of this lack of data. This introduction to the chapter is followed by the following sections – an overview of the concept of immigrant integration and its dimensions; a look at Punjabi/Sikh immigration to Canada through the years and dimensions of economic, social, cultural and political integration for the Punjabi/Sikh community. The chapter concludes with a discussion of the findings. Punjabi/Sikh immigration to Canada through the years The early Punjabi migrants to Canada were largely Sikhs with little education from the Indian districts of Jalandhar, Ferozepur, Ludhiana, Amritsar and Gurdaspur (Verma, 2003). These early migrants came to Canada in the early 1900s with dreams of a more secure financial future for their families – primarily through remittances – than what they faced in Punjab (Manak, 1998; Singh, 1994). The caste groupings prevailed even in Canada in the early years and determined the immigrants’ cultural practices in their host country (Verma, 2003). Sikhism continues to grow in Canada due to the continued immigration of Punjabis over the years. O'Connell (2000) divides the history of Sikhs in Canada into two broad periods – the early to mid-1900s and then the period from 1960 till current days.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.027 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".