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Record W2142066229 · doi:10.17722/ijrbt.v6i1.381

Human Computer Interactions (HCI) Design for Sustainable Global Development: A Review of the Literature

2015· review· en· W2142066229 on OpenAlexvenueno aff
Titus Tossy, Sekione Reward Jeremiah

Bibliographic record

VenueInternational Journal of Research in Business and Technology · 2015
Typereview
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceHuman–computer interactionSustainable developmentPolitical science

Abstract

fetched live from OpenAlex

Human Computer Interactions (HCI researchers have contributed numerous articles in the area of sustainability; however, much of this work is skewed towards environmental sustainability. Future HCI research must take a more comprehensive view of the environmental, social, and economic facets that make up sustainability. HCI is central to the idea of designing for development and sustainability. This paper defines sustainability and each of the three facets, reviews existing HCI research that overlaps with these facets, and suggests directions for HCI to help achieve sustainability in the future. This paper examines the evolving role of HCI for sustainable development and therefore propose the idea that researchers in HCI have to strive for a greater balance between attempting to produce global and local knowledge. The paper concludes with a set of remaining questions to consider for future HCI research in sustainability.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.862
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.143
GPT teacher head0.476
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2015
Admission routes1
Has abstractyes

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