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Our Future Mind: Epochal Developments of Perinatal Clinical Psychology

2014· article· en· W1977900935 on OpenAlexvenueno aff
Antonio Imbasciati

Bibliographic record

VenueInternational Journal of Child Health and Nutrition · 2014
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychoanalysisEpistemologyPsychology

Abstract

fetched live from OpenAlex

This paper clarifies the meaning of Perinatal Clinical Psychology by removing the prejudice and the stereotypes that unfortunately pervade children health care facilities still nowadays. The author goes over the basic principles that neuroscience has recently demonstrated in the development of the brain from the fetus to the infant, the child and the adult. The brain is self-generating through experience and not on the basis of genome. Epygenetics accounts for it. The brain needs to learn so as to be able to develop. Nobody has a brain that is the same as anybody else’s and therefore nobody has a mind that is the same as anybody else’s. The brain generates the mind and, in turn, the mind regenerates the brain in a ceaseless feedback. The experience that generates and renews the brain continuously comes from interpersonal relationships. The greatest incidence of this kind of development comes from the relationships with the parents and the caregivers and depends on the emotional moment of the relationship. This opens up transgenerational perspectives. The quality of the mind (and the brain) of the parents and caregivers produces the quality of the mind of the children. The latter, in turn, become adults, condition the mind of their children in cascade effect from one generation to the following. This transmission can produce an improvement but also a worsening for the future generations. As a consequence, Perinatal Clinical Psychology becomes important for prevention and psychological support to the children and the families at risk.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.511
Teacher spread0.432 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2014
Admission routes1
Has abstractyes

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