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Record W2914979181 · doi:10.1177/1523422319827938

The Roles of Sufi Teachings in Social Movements: An HRD Perspective

2019· article· en· W2914979181 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Developing Human Resources · 2019
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsFanshawe College
Fundersnot available
KeywordsPerspective (graphical)Civil societySociologyContext (archaeology)Resource mobilizationSocial movementSufismEnvironmental ethicsPhenomenonPublic relationsEpistemologyPolitical scienceLawIslamPhilosophyTheology

Abstract

fetched live from OpenAlex

The Problem There is a growing need to explore the role of the centuries-old tradition of Sufism and its teachings which, through social movements, have contributed to, and continue to influence, human resource development (HRD) at various levels—individual, group, organization, community, nation, and international. The Solution To address this need, we present cases of social movements inspired by Sufi teachings in selected parts of the world. We discuss, using literature and personal experiences, links among Sufi teachings, social movements, and HRD, and provide a framework for understanding Sufi teachings within the context of the social movement phenomenon. We end with recommendations for practice and research. The Stakeholders We target broadening the horizons of HRD researchers, practitioners, civil society members, and social movement activists, encouraging them to address long-term changes and collective learning through the quest for unconditional love and liberation, which represent the core of Sufi teachings.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.374
Teacher spread0.350 · 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