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Record W2528105234 · doi:10.5750/ejpch.v4i3.1214

Updating the descriptive biopsychosocial approach to fit into a formal person-centered dynamic coherence model - Part III: Personhood, salutogenesis and further topics

2016· article· en· W2528105234 on OpenAlexaff
Thomas Frölich, F F Bevier, Alicja Babakhani, Hannah H Chisholm, Peter Henningsen, David S. Miall, Seija Sandberg, A. Schmitt

Bibliographic record

VenueEuropean Journal for Person Centered Healthcare · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterpretation (philosophy)EpistemologyInterpreterPersonhoodMeaning (existential)Set (abstract data type)Computer scienceCoherence (philosophical gambling strategy)PsychologyCognitive scienceSociologyCognitive psychology

Abstract

fetched live from OpenAlex

In the present paper the approach, as outlined in our previous articles, is applied to a range of subjects. Its main goal is to understand how human specifics such as use of language, cultural creativity, rational thinking and the use of abstractive terms interfere with human beings basic organic processes. This necessitates an examination at the level of semantics. The latter is referred to as the relationship of produced states to a meaning so that from a sender’s side they are meant to transport meaning from a receiver. Since an interaction of two distinct entities is at issue here, we have to describe the interaction in formal terms, so we talk about the hypostasising of a triggering contact of one entity’s change of states initiating a change of states of another entity. This contact can be accepted as a trigger or not as a trigger, a decision that corresponds to the most primitive form of (possibly also mutual) interpretation. With this model in mind, we can interpret different communicative settings, as the monomeric self-efficacy interpretation, or mutual interpretations in families. To interpret needs a physically memorised categorisation. Only this allows for fast and set-related attributions. Such categorisations can go wrong, especially in fast changing environments. If a higher resolution is needed, additional distinctions are implemented into the heuristic interpretative procedures. Human beings have additional tools for higher resolution in differentiation: practical segmentation and speaking. Afterwards, the products of material and logical discretisation may be re-combined into a new arrangement. The corresponding accessory potential helps to generate a world of its own, as a full-grown personhood. Human uniqueness hence is based on the individuality of each person’s material basis, as well as on its individual type of differentiation and corresponding attribution. Being aware of this, the also mental individuality allows to understand self-interpretative processes that support salutogenesis and an experience of being self-efficient, or not.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.024
Scholarly communication0.0050.011
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.203
GPT teacher head0.397
Teacher spread0.194 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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