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Record W4411882557 · doi:10.5539/jel.v14n6p197

Navigating Spiritual Turmoil in the Doctoral Journey: An Autoethnographic Perspective

2025· article· en· W4411882557 on OpenAlexvenueno aff
Anirutt Somsao, Ariyabhorn Kuroda

Bibliographic record

VenueJournal of Education and Learning · 2025
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)AutoethnographySociologyPedagogyPsychologyGender studiesVisual arts

Abstract

fetched live from OpenAlex

Spiritual turmoil, often overlooked in academic discourse, challenges identity, purpose, and meaning. This study explores spiritual turmoil through autoethnographic research, grounded in the researcher’s lived experiences during a doctoral journey. It addresses the gap in understanding the existential dimensions of learning and growth. Findings reveal that spiritual turmoil emerges gradually, influenced by life transitions, emotional stress, and existential uncertainties, often amplified by academic pressures. Key manifestations include a loss of meaning, social withdrawal, emotional and identity confusion, and questioning of values and purpose. In academic settings, this turmoil intersects with learning, as high workloads, misaligned personal and institutional goals, and competitive environments intensify its effects. While disrupting academic focus, spiritual turmoil acts as a catalyst for self-discovery, fostering psychological transformation, deeper reflection, and the realignment of personal and academic objectives. This research underscores how crises of meaning, though distressing, lead to renewed purpose and intellectual growth. By integrating autoethnographic insights with an exploration of spirituality in academia, the study offers a unique lens on navigating inner conflict and renewal. It provides valuable implications for educators, researchers, and learners, highlighting the transformative potential of spiritual turmoil in reshaping the intersection of education, personal growth, and existential meaning.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.609

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 science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.405
Teacher spread0.377 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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