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Enregistrement W2619561911 · doi:10.1093/humrep/dex107

Disclosure and donor-conceived children

2017· letter· en· W2619561911 sur OpenAlexaff
Marilyn Crawshaw, Damian Adams, Sonia Allan, Eric Blyth, Kate M. Bourne, Claudia Brügge, Anne Chien, Antonia Clissa, Ken Daniels, Ellen Sarasohn Glazer, Jean M. Haase, Karin Hammarberg, Hans van Hooff, Jennie Hunt, Astrid Indekeu, Louise Johnson, Young Jin Kim, Maggie Kirkman, Wendy Kramer, Ann Lalos, Charles Lister, Phyllis Lowinger, Erica J. Mindes, Jim Monach, Olivia Montuschi, Sheila Pike, Victoria Powell, Iolanda S. Rodino, Alice Ruby, Anne Schrijvers, Yukari Semba, Ruth Shidlo, Petra Thorn, Lois Tonkin, Marja Visser, Julia T. Woodward, Tewes Wischmann, Samantha Yee, Julianne E. Zweifel

Notice bibliographique

RevueHuman Reproduction · 2017
Typeletter
Langueen
DomaineMedicine
ThématiqueReproductive Health and Technologies
Établissements canadiensCReATe Fertility CentreOttawa Fertility CentreVictoria Hospital
Organismes subventionnairesnon disponible
Mots-clésDonor inseminationMedicinePregnancyBiologyGenetics

Résumé

récupéré en direct d'OpenAlex

Sir, Guido Pennings’ views on favouring donor anonymity are well known. However we were very concerned at your decision to publish and then highlight his article Disclosure of donor conception, age of disclosure and the well-being of donor offspring (Pennings, 2017) which, in our view, fell significantly short of the academic rigour we expect of Human Reproduction and its peer review and editorial processes. The signatories to this letter come from the fields of academia, professional practice, parent/family/donor-conceived support groups and donor registry services. The research evidence concerning the impact of disclosure and age of disclosure on donor-conceived people and their family members is very limited, both in terms of numbers and range of participants, numbers of research teams working in this field and methodologies used, including sampling across all studies. There are to date no large-scale studies. This was not made clear: more than this, Pennings considered that the evidence was in fact sufficient to make claims based on it, not least through disproportionately weighting selected studies and ones which used primarily parental reports (which form the bulk of existing studies) over those from donor-conceived individuals, which he claimed used biased samples. He went on to attribute morality (‘parents should disclose’) rather than knowledge as the reason Kovacs et al. (2015) and the Nuffield Report (2013) recommended disclosing. In doing so, he ignored Nuffield's emphasis on adolescent psychological development as a key plank of their decision and Kovacs et al.’s attention to the Australian cultural context. With regard to the latter, Pennings instead chose to represent this approach as being so at odds with their findings as to question their motivation as researchers (‘One wonders why they have done the study in the first place’) rather than acknowledge its validity. Unlike Pennings, some of those he singled out for criticism thoughtfully discuss the complexity of measuring outcomes as evidenced by, for example, Freeman and Golombok (2012) when they said: ‘However, differences between disclosing and non-disclosing families cannot be directly attributed to parents’ disclosure decisions and may reflect other differences between these families’. Both for these reasons and because research evidence only forms one part of what informs theory, policy and practice in any field—and perhaps especially where human relationships are concerned—the basic premise of Pennings’ paper is in our view academically flawed. Pennings omitted any reference at all to human rights, despite this being a key influence on change in this field as shown in current legislative moves in Germany, and dismissed personal experiences when captured through the grey literature or professional experience. Finally, and importantly, Pennings ignored the actual and potential impact of recent rises in DNA testing, including direct-to-consumer DNA testing, on the ability to maintain secrecy about involvement in donor conception given the resulting increased likelihood of unplanned disclosure and its associated risks (risks which Pennings chose largely to ignore). This despite a paper by Harper et al. (2016)‘The end of donor anonymity: how genetic testing is likely to drive anonymous gamete donation out of business being an earlier Human Reproduction ‘Editor's Highlight’ in 2016. Pennings went on to make critical remarks about counsellors and psychologists, ironically without citing any evidence to substantiate his claims and in the process minimizing multi-disciplinary support for openness as evidenced though such professional bodies’ guidelines as the American Society of Reproductive Medicine, the British Fertility Society, and the Australian and New Zealand Infertility Counsellors Association (ANZICA). His suggestion that counsellors and psychologists should be training parents who do not wish to disclose to ‘build a coherent and easy to maintain story’ is especially troubling; it is one thing to be expected to respect parents’ decisions (which psychosocial professionals do, in our experience), it is entirely another to expect them to teach parents how to lie to their children. Of course academics have the right to prompt debate and discussion on such important topics as disclosure and anonymity and we strongly respect that right; our concern here is that this paper has not met the standards that we would have expected from Human Reproduction.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,038
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,038
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0030,003
Communication savante0,0030,002
Science ouverte0,0010,001
Intégrité de la recherche0,0170,016
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,320
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations23
Publié2017
Routes d'admission1
Résumé présentoui

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