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Adaptive Facilities for Supporting Differently-abled Persons in the Library Environment: A Case Study of Libraries in Shillong, Meghalaya, India

2015· article· en· W2619805335 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSRELS Journal of Information Management · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsScience North
Fundersnot available
KeywordsBrailleProcess (computing)Variety (cybernetics)Library scienceBusinessComputer scienceOperating system

Abstract

fetched live from OpenAlex

The differently-abled are emerging as a force that cannot be ignored today. While the capabilities of many of these are almost at par with and sometimes even surpass those of the 'abled', their special needs cannot also be denied. Public institutions of all kinds have geared up or are in the process of gearing up to facilitate the smooth movement and functioning of this group, with a variety of facilities, from general ones such as crutches, elevators, ramps, braille, hearing aids etc. to more specialized ones such as CUPID, Dexter etc. Libraries worldwide have also put many of these adaptive facilities in place. This study set out to explore whether libraries in Shillong, North East India, provide adaptive facilities for supporting the differently-abled. The study found that the libraries in Shillong are grossly under-equipped in this regard and that excuses abound. Reasons for not having adaptive facilities for the differently-abled range from lack of funds to 'absence of differently-abled patrons'- a claim that exposes the lack of planning on the part of the libraries. It was found however, that some Library staff members do realize the significance of the differently-abled and the need for facilitating their functioning in the Library 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.271
Teacher spread0.217 · 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