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Record W4413366254 · doi:10.31219/osf.io/bp2vf_v1

What I Sense, How I Feel: The Classroom Sensory Environment from the Perspective of Children with Sensory Needs

2025· article· en· W4413366254 on OpenAlexfundno aff
Jessica Massonnié, Theodora Mavridou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsnot available
FundersFederation for the Humanities and Social SciencesUniversity of Portsmouth
KeywordsPerspective (graphical)Sensory systemPsychologyAestheticsCognitive psychologyArtVisual arts

Abstract

fetched live from OpenAlex

This study, co-designed with educational professionals, uniquely investigated how twenty-three primary school children identified as having sensory needs perceive their classroom sensory environment. It adopted a needs-based, transdiagnostic approach and covered seven senses. Applying framework analysis on semi-structured interviews, it uncovered the biological, psychological and social factors underlying children’s response to sensory input, and its perceived effects on learning. In particular, results emphasised the importance of the meaning, memories and social dynamics attached to sensory input, which are not systematically considered in conceptual frameworks of sensory processing. Responses to sensory input were therefore not characterised in absolute terms but were dependent on the specific time, space and individuals involved. The thematic map generated from this study can be used as a reflexive framework to support collective discussions (which may involve researchers, education professionals, families and children) on the factors influencing children’s response to sensory input in a classroom environment.

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)0.005
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: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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
Published2025
Admission routes1
Has abstractyes

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