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Record W7154810150

Adoption’s need for ‘villains’: folklore, [legal] fictions, and Northern Ireland’s proposals for redress

2024· article· en· W7154810150 on OpenAlexaboutno aff
Alice Diver

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRedressIdentity (music)Public opinionTrope (literature)Property (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Adoption lore (found in its laws, policies, and jurisliterature, for example) often seems to demand - or indeed conjure - the presence of a villainous other. Archaic beliefs and customs have long sought to vilify the various participants in adoption processes, legal and de facto: adoptees and foundlings may be depicted as 'demon seeds' or suspect, abhuman changelings, ‘relinquishing’ parents may be framed as indifferent or feckless abandoners, while the ‘wicked stepmother’ trope continues to predominate in folk and faery tales, and in popular culture. More recently, the decision-makers behind a century of forced adoption practices (human, church, state) have gradually been identified as particularly culpable, in several jurisdictions where truth recovery or redress mechanisms are slowly grinding to a conclusion (e.g. Ireland, Australia, Canada, England and Wales) or indeed struggling to get fully off the ground (Northern Ireland, Korea). The ‘shapeshifting’ nature of the villainous other’s role and identity merits analysis, given its ability to influence public opinion and cause mini moral panics. I argue here that Northern Ireland’s current Consultation on the need for a Public Inquiry (and redress scheme) for the victims and survivors of mother baby institutions (and Magdalen Laundries, and potentially, workhouses) contains clear and subtle echoes of some of the more concerning traditions and tropes on forced relinquishment. Its emphasis, for example, on the stigmatising need to maintain secrecies and protect property interests (inheritances of potential awards, preservation of public funds) may prove particularly triggering for older adoptees long-affected by brick-walled searches for identity and ancestors, reunion refusals, informational vetoes, or advice on the need for rescue-gratitude and deferential behaviours.

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)0.015
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0170.069
Scholarly communication0.0160.008
Open science0.0030.009
Research integrity0.0080.014
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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