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Record W7024100176

Project Accessibility Reflection Paper

2022· other· en· W7024100176 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoiceAbleismVariety (cybernetics)Reflection (computer programming)DisadvantagedPhoto elicitationEconomic JusticeAssistive technology
DOInot available

Abstract

fetched live from OpenAlex

This research considers the experiences of seven students with physical disabilities navigating physical, education and social barriers in their respective schools located in south and central Ontario. Gathering first-hand experiences was my first step towards designing and establishing a pilot project centered around better integration of students with disabilities into high school. By working with students in grade 10-12, this research invited seven participants to identify the physical, social, and educational barriers they experienced, through two workshop sessions. I introduced disability justice as a useful concept for students to reflect on issues of ableism and used photovoice as a tool for students to share their thoughts and concerns about their school environments. Employing photovoice as a research method offers students a combination of photos and words to express their experiences and identify important issues. In my workshop, I had the participants take photos in and around their schools to document the barriers they encountered daily. There were a variety of barriers highlighted by the students; some were obvious, such as stairs, lack of accessible washrooms, and poor maintenance of the landscape surrounding the school. While less obvious ones were the social and educational barriers such as a lack of access to sports clubs, interaction with peers, and a lack of opportunities to learn about disability in coursework. Throughout the research, students proposed recommendations such as; regular maintenance of elevators and landscape, reduced number of desks in classrooms, and more accessible clubs free of barriers, to name a few. These findings reflect a system in need of change; a system that, with the right amount of care and attention can open itself up to reach a wider body of people and allow them to receive the education they deserve.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.376
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.002
Scholarly communication0.0090.006
Open science0.0020.013
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3760.117

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 head0.203
Teacher spread0.183 · 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.

Study designNot applicable
Domainnot available
GenreOther

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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