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Record W2791854342 · doi:10.2166/wpt.2018.002

The role of adaptation in mobile technology innovation for the water, sanitation and hygiene sector

2018· article· en· W2791854342 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

VenueWater Practice & Technology · 2018
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSanitationHygieneBusinessAdaptation (eye)Conceptual frameworkMobile technologyEnvironmental planningEngineeringEnvironmental engineeringGeographyTelecommunicationsMobile computingMedicineSociologyPsychology

Abstract

fetched live from OpenAlex

Abstract While the growing availability of mobile phones has commanded the attention of the development community, an estimated 844 million people continue to lack access to basic drinking water and 2.3 billion to adequate sanitation. Development has now begun of mobile applications to improve access to water, sanitation and hygiene services (mWASH). To understand the barriers to innovation, nine mWASH applications were studied using the Framework for Analyzing a Multi-level Innovation System (FAMIS), a conceptual model. Applying FAMIS to a technology aids in understanding when and why it succeeds or fails, and how key stakeholders and institutions can be targeted for intervention. The analysis highlights ways to overcome barriers to innovation and suggests that the technology is less important than the way in which it is implemented.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.270
Teacher spread0.251 · 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