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Record W7128347739

Prevention of children risk bahaviours in interactions with dogs

2022· dissertation· cs· W7128347739 on OpenAlexaboutno aff
Jan Náhlík

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2022
Typedissertation
Languagecs
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBreedAnimal welfareHUBzeroLabrador RetrieverPsychological interventionAnimal-assisted therapy
DOInot available

Abstract

fetched live from OpenAlex

Dog attacks on children are a widespread problem, which can occur when parents fail to realise a potentially dangerous interaction between a dog and a child. The aim of the study was to evaluate dogs attacks to children in Czech households, the ability of parents to identify dangerous situations from several everyday child - dog interactions, determine whether the participants connected these situations to a particular breed of dog and whether participants intend to participate in the dog bite preventing program for them and their children. Data were presented via an online survey to parents of children no more than 6 years old. Data from 208 respondents were analysed using procedure GLIMMIX in SAS program, version 9.3 and Pearson's Chi-squared test in program "R". We recorded 19 dogs attacks on children and children always knew attacking dog. Parents were present and supervised 18 children when attacks happened. Three children had to receive medical help after being attacked by a dog and one developed a post-traumatic stress disorder - a phobia of dogs. Most participants would welcome educating programs about child - dog interactions, more often those who owned a dog (p 0,05). The probability of risk assessment varied according to dog breed (p 0.001) as well as to the depicted situation (p 0,001). Results indicated that Labrador Retriever was considered the least likely of the three dogs to be involved in a dangerous dog - child interaction (with 49 % predicting a dangerous interaction), followed by Parson Russell Terrier (63.2 %) and American Pit Bull Terrier (65 %). Participants considered one particular dog-child interaction named 'touching a bowl' a dangerous interaction at a high rate (77.9 %) when compared with the other presented situations, which were assessed as dangerous at rates of 48.4 % to 56.5 %. The breed of dog seems to be an influential factor when assessing a potentially dangerous outcome from a dog - child interaction. Contrary to our hypothesis, interactions involving the small dog (Parson Russell Terrier) were rated more critically, similarly to those of the American Pit Bull Terrier. These results suggest that even popular family dog breeds, such as Labrador Retrievers, should be treated with more caution.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.299
Teacher spread0.293 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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