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Record W4411170427 · doi:10.17161/gjcpp.v14i2.21035

Analysis of the accessibility of perinatal and early childhood services for parents with physical disabilities: A modelled reading of access barriers

2023· article· en· W4411170427 on OpenAlexaff
Coralie Mercerat, Thomas Saïas

Bibliographic record

VenueGlobal Journal of Community Psychology Practice · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsReading (process)PsychologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Perinatal and early childhood services are valuable resources for all new parents, particularly in supporting them as they transition to their new role. However, parents with physical disabilities report several barriers to accessing these services, including difficulty physically accessing services, lack of knowledge or negative attitudes of professionals, and lack of adaptation of services. The objective of this article is to analyse, through the Dixon-Woods et al. accessibility model, the barriers to accessing perinatal and early childhood services from the perspective of parents with physical disabilities. Thirteen semi-structured individual interviews, using the life story approach, were conducted. The results highlight barriers to access to services in all dimensions of the accessibility model. Principal barriers reported include non-inclusive criteria for accessing services (taking account both parenthood and disability), lack of knowledge about the services offered and the inadequacy of services in addressing parents’ needs. The sixth dimension (“offers and resistance”) presents a dynamic element, as it relates to the parents’ decision to use – or not – a service to which they are entitled. Using this model allowed for a pragmatic and systematic description of the obstacles encountered by parents, as well as the identification of needs and potential directions for action.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.455
Teacher spread0.387 · 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 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
Published2023
Admission routes1
Has abstractyes

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