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Record W4411639306 · doi:10.69470/q5e6wc19

TRANSFORMING THE PRESENCING SELF

2025· article· en· W4411639306 on OpenAlexaff
Olen Gunnlaugson

Bibliographic record

VenueInternational journal of presencing leadership & coaching. · 2025
Typearticle
Languageen
FieldPsychology
TopicEgo Development and Educational Practices
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

This article introduces a new phenomenological movement that deepens and transforms the presencing self through developmental shifts in awareness and being. Central to this inquiry is the mesa-turn, an embodied ontological shift that extends Robert Kegan’s subject-object theory of development. Whereas Kegan’s meta-shift emphasizes transformation in one’s self understanding through cognitive decentering and perspectival awareness, the mesa-turn invites practitioners into reclaiming deeper levels of ontological embodiment as a basis for presencing mastery. Drawing from Dynamic Presencing (DP) (Gunnlaugson, 2020-2025), this inward reorientation cultivates direct, somatic contact with the presencing self. This deepening unfolds through the Threefold Developmental Movement: 1) the meta-shift, which uncovers the presencing self through a perspective-taking process; 2) the mesa-turn, which re-roots practitioners in the embodied depths of their presencing nature; and 3) unitive resting, which anchors them in a deeper integrative state of being presence. Together, these three movements reconfigure one’s relationship with their presencing self by guiding a progression from dis-identification (meta-shift) to embodied re-identification (mesa-turn) to a re-configured, integrative identification within presence itself (unitive resting). This framework opens new developmental horizons for presencing leaders, coaches, and practitioners by shifting presencing beyond a way of knowing into a generative and sustained way of being.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.023
Scholarly communication0.0060.011
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.091
GPT teacher head0.386
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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