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Record W2528428944 · doi:10.5750/ejpch.v4i3.1213

Updating the descriptive biopsychosocial approach to fit into a formal person-centered dynamic coherence model - Part II: Applications and some more basics

2016· article· en· W2528428944 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
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoherence (philosophical gambling strategy)PsychologyBiopsychosocial modelReading (process)PsychicCognitive psychologyEpistemologyCognitive scienceLinguisticsPhilosophyPsychotherapist

Abstract

fetched live from OpenAlex

There is an undeniable difference of approaches in science and humanities. Any model that claims to unify these different approaches must prove to be in accordance with both the objectivistic and the subject-oriented thinking. In the following article we first check our models applicability in two areas that belong to our individual research expertise: biochemistry (TF) and narratology (DSM). Then we try to understand how – be it on a microscopic, e. g. biochemical, be it on a macroscopic body and mind level – distinct coherences manage to survive in a partially or mostly random environment. As an example we address children who grow up in an environment that lacks coherence and hence predictability. Studies have shown that these children are forced to improve their detective “mind-reading” ability. So, with regard to even minute signs that might help them to get information about coherences within their families system their sensitivity is more than average. But on the other hand, and on the long run, these children may have a higher risk to later develop a psychic disorder such as a “borderline syndrome”. The idea behind our approach in that instance is that human beings consist of coherences and to “survive” (in a both literal, bodily and a metaphoric, mental and spiritual sense) correspondingly are in need for continuous supportive feed in form of outside coherences. Each word that could be established in a babies or child’s memory then is and acts as a little organiser to recognise and understand outside and later inside coherences. This starts as soon as it can be reliably used for attributions, and it gradually results in establishing a “narrative self”. Both the bodily and the narrative self are in permanent danger of being corrupted or even deleted by random, unpredictable and unforeseen processes. To survive, not only the material basis must be kept alive, but also the correct timing of its individual processes. To destroy an interior timing may be much easier than to destroy a material basis. One only has to interrupt internal or external communication to achieve this goal. In the following, we discuss the prerequisites and formal aspects of a successful interior and external timing. Then, we first try to overcome misleading spatial metaphors as used for aspects that are mainly time-based, and then differentiate two types of timing in information processing: a “quick and dirty” and a slow and refined one. The latter differentiation is discussed in Daniel Kahnemans well known book “Thinking, Fast and Slow. To understand how a person perceives, interprets and acts we, to our believe, need to differentiate between these two basically different systems. Doing so, we gradually come to an understanding of personhood and subjectivity that is in accordance with our basic model, and also, though taking aspects like narrativity into account, with our bodily processing.

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)0.007
metaresearch head score (Gemma)0.010
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 score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0030.027
Scholarly communication0.0070.019
Open science0.0030.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0150.002

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 head0.148
GPT teacher head0.354
Teacher spread0.207 · 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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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