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Record W2964062870 · doi:10.1163/15685306-12341566

Significance of Horses: Control Legislation and Impact on Irish Travellers

2019· article· en· W2964062870 on OpenAlexaff
Patricia Burke Wood

Bibliographic record

VenueSociety and Animals · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsIrishContext (archaeology)LegislationLivestockGeographyPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

Abstract This paper documents the significance of horses to Irish Travellers, on several fronts, to demonstrate their unusual relationship with horses as companion animals and as work animals in a non-farm context. Their multiple attachments and engagement are analyzed in the context of the literature in human–nonhuman animal relations and animal geographies, which helps illuminate the ways in which horses have shaped Traveller geographies and identities, and how these associations have become politicized. The 1996 Control of Horses Act has led to greater restrictions on the keeping of horses; the impact of the loss of this animal from Traveller daily life is discussed. This research also helps fill a gap in the literature on horses and urban and rural landscapes in Ireland, which has to date largely excluded Travellers.

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)0.003
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.020
GPT teacher head0.315
Teacher spread0.295 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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