Updating the descriptive biopsychosocial approach to fit into a formal person-centered dynamic coherence model - Part II: Applications and some more basics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".