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Capacity Building for Different Abilities Using ICT

2012· book-chapter· en· W2484068453 on OpenAlexaff
Ina Freeman, Aiofe Freeman

Bibliographic record

VenueIGI Global eBooks · 2012
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInformation and Communications TechnologyPopulationWork (physics)BusinessPublic relationsEconomic growthMarketingPsychologyEngineeringPolitical scienceMedicineEconomicsEnvironmental health

Abstract

fetched live from OpenAlex

Social enterprises are expected to contribute to the well-being of society. One way this is done is through assisting individuals to become productive citizens. For those enterprises that work with individuals with disabilities, this is accomplished through education and assistance with various daily tasks. The disability population is increasing as the population ages and faces an increased potential for disability through disease and biological events as well as higher rates of diagnosis of developmental disability throughout the life span. When coupled with the increasing integration of individuals with disabilities into the community, there is a greater need for ways by which these individuals are included and supported. While technology is prevalent in today’s society, there is little training for those working with clients and little money to purchase the technology, leading to limited access. With few purchasers, little effort is expended to enhance the accessibility of existing technology and create more productive forms of technology. To decrease the costs to society, the role of social enterprises might research the necessary technology to further develop and facilitate the engagement of individuals with disabilities into society.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.067
GPT teacher head0.257
Teacher spread0.190 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2012
Admission routes1
Has abstractyes

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