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Enneagram Personalities

2011· book-chapter· en· W4246047811 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

VenueIGI Global eBooks · 2011
Typebook-chapter
Languageen
FieldPsychology
TopicEgo Development and Educational Practices
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsPersonality psychologyPersonalityPsychologySet (abstract data type)Function (biology)Variety (cybernetics)PsychoanalysisComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Recalling the definition of personality as “a complex set of relatively stable behavioral and emotional characteristics,” we can appreciate the insights provided by the Myers-Briggs system. However, we are equally aware that no one system can hope to address all aspects of personality. A noteworthy personality analysis tool that has achieved a significant presence in both personal growth and management applications is the Enneagram system of personalities. The essence is said to have descended from the ancient Sufis, and modern adaptations have been made by a variety of authors, including Riso (1990), Condon (1997), Palmer (1998), Rohr and Ebert (1990), and Goldberg (1996). Whereas MBTI attempts to explain how we function, the Enneagram focuses more on why we function in a particular way—what is our underlying emotion that guides the way we act? In this way, MBTI and the Enneagram can be viewed as complementary.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.447
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.009

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 head0.074
GPT teacher head0.324
Teacher spread0.250 · 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