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Record W2619561911 · doi:10.1093/humrep/dex107

Disclosure and donor-conceived children

2017· letter· en· W2619561911 on 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

Bibliographic record

VenueHuman Reproduction · 2017
Typeletter
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsCReATe Fertility CentreOttawa Fertility CentreVictoria Hospital
Fundersnot available
KeywordsDonor inseminationMedicinePregnancyBiologyGenetics

Abstract

fetched live from 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.

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)0.005
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.017
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0170.016
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.320
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations23
Published2017
Admission routes1
Has abstractyes

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