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Record W4281390254 · doi:10.7202/1088852ar

L’identité narrative dans la prise en charge psychologique des jeunes issus de la conception médicalisée

2022· article· en· W4281390254 on OpenAlexaffvenue
Delphine Rambeaud-Collin, Yann Zoldan

Bibliographic record

VenueRevue Jeunes et Société · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsNarrativeContext (archaeology)Identity (music)PsychologyTimelineNarrative identityNarrativityPerspective (graphical)AestheticsHistoryLiteratureArtVisual arts

Abstract

fetched live from OpenAlex

The story of becoming a parent is often couched in the language of desire built on fantasies. And although such idyllic accounts tend to conceal much more difficult stories about becoming parents, nevertheless assisted reproductive technology has given new hope to many couples experiencing infertility. In the course of our work as professional psychologists, we recorded the reflections of young women between the ages of 15 and 25 who were conceived using assisted reproductive technology. To understand how the circumstances of their conception impacted their narrative identity, we adopted a clinical approach that involved having these young women share their life narratives, starting with their conception stories. Based on our clinical observations, the article explores a five-stage method for facilitating narrativity, consisting of the interview process, projective mechanisms, the creation of an autobiographical timeline, and, finally, the act of writing a life story. This multifaceted approach makes it possible to address the impact of conception stories on narrative identity from both a diachronic and synchronic perspective. Finally, we conduct a theoretical and clinical assessment of this promising methodology, which primarily aims to give young people the tools and support they need to share their life narratives in the context of therapy sessions—a process likely to promote better mental health through more harmonious identity development.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.293
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.384
Teacher spread0.352 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

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