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Record W40830286

Previous semen donors and their views regarding the sharing of information with offspring

2005· article· en· W40830286 on OpenAlexaboutno aff
Ken Daniels, Eric Blyth, Marilyn Crawshaw, Ruth Curson

Bibliographic record

VenueUniversity of Huddersfield Repository (University of Huddersfield) · 2005
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsOffspringQuarter (Canadian coin)Sperm bankGovernment (linguistics)Family medicineMedicinePsychologySocial psychologyPregnancyFertilityBiologyPopulationEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

The UK government has decided to introduce, from 2005, rules that will allow donor-conceived persons to have access to identifying information concerning their donor. This has led to many concerns regarding future gamete donor recruitment. METHODS: Semen donors who had been recruited between 1988 and 2002 were invited to take part in a telephone interview. The interview sought these previous donors’ views on issues associated with recruitment, attitudes regarding information sharing and views concerning the offspring. Responses regarding information sharing were compared with their views recorded at the time of recruitment. RESULTS: All 32 donors were recruited altruistically. Eighteen (56%) held the same views concerning the provision of identifying information as they did at the time of recruitment. Of those who had changed their views, eight (25%) expressed a willingness to be more open and four (12%) now wished to be anonymous having previously been unsure. Half of the donors would still have donated if they had been required to be identified to offspring, one-quarter would not have and one-quarter were undecided, although the majority of these said they may have donated under an open system. CONCLUSION: The study shows that it is possible to recruit identifiable donors at this clinic and this suggests that it may be possible for other clinics to do likewise.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.191
Teacher spread0.178 · 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 designQualitative
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

Citations13
Published2005
Admission routes1
Has abstractyes

Explore more

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