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Record W7053372659

University Students' Perceptions of Learning Disabilities

2025· dissertation· en· W7053372659 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2025
Typedissertation
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionArticular cartilage damageDysgeusiaGestational periodHyporeflexiaFilter (signal processing)
DOInot available

Abstract

fetched live from OpenAlex

Special education has been widely explored as the prevalence of learning disabilities (LD) has become extremely relevant (Statistics Canada, 2016). Therefore, it is important to gain a deeper understanding of the terminology special education and inclusive education, to promote further awareness of how it can be impactful to students with LDs learning. Special education exists to support individuals with LDs who benefit from specialized learning plans, to help facilitate and enhance their learning (Street, 2004). The essence of inclusive education is to ensure that diversity is supported and celebrated by each unique learner (UNESCO, 2008). An LD can be referred to as a group of heterogeneous disorders which may impact an individual's organization skills, retention, comprehension, or use of verbal and non-verbal information (Learning Disabilities Association of Canada, 2016). This qualitative narrative inquiry approach investigated how students within Southern Ontario with a learning disability diagnosis story and perceive their learning and their access to support at the university level. Semi-structured interviews were implemented to gather meaningful data (van den Hoonaard, 2018). The results revealed the challenges that participants faced due to their LDs, such as stigmas associated with LDs and the obstacles they overcame while receiving accommodations. To conclude, policies and regulations need to be implemented to not only help educate faculty regarding accommodations but also find ways to enhance the services provided to students.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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