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Record W7014898250

Raj Karega Khalsa! - The Evolution of the Sikh Identity

2022· article· en· W7014898250 on OpenAlexaboutno aff

Bibliographic record

VenueUSF Scholarship Repository (University of San Francisco) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandIdentity (music)TimelinePower (physics)Face (sociological concept)PopulationKey (lock)Faith
DOInot available

Abstract

fetched live from OpenAlex

Generally, religion has served as a method of creating a unique identity and history for many groups across history. This concept is especially true for the Sikh community, to the point that they have carved their own niche across the different places they inhabit in the world, whether that be their homeland of Panjab or their extensive population in places like Canada or the United Kingdom. However, this expansion and development of their culture did not come without a cost, formed through countless battles, martyrdom, and revolutions. Chardi Kala, a foundational idea in Sikhi that refers to eternal optimism even in terms of adversity, shows why they are prepared to face severest torture and martyrdom willingly, a unique concept created by the religion (Singh 2002). This literature review examines the history and social factors that contributed to the aforementioned concept and others mentioned in Sikh philosophy. It will go through key moments in the Sikh timeline that will help to explain this distinct identity and how it has evolved into the current day. Additionally, it will help to illustrate the way that cultures can thrive even in the face of severe adversity, sometimes through the simple power of hope and trust in one’s faith.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.185
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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