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Record W2795073795 · doi:10.1177/1468017318767091

Readability, suitability, and writing for clients with limited literacy skills

2018· article· en· W2795073795 on OpenAlexfundno aff
Natalie Ames

Bibliographic record

VenueJournal of Social Work · 2018
Typearticle
Languageen
FieldComputer Science
TopicText Readability and Simplification
Canadian institutionsnot available
FundersMcGill University
KeywordsReadabilityLiteracyPsychologyReading (process)Computer sciencePedagogyLinguistics

Abstract

fetched live from OpenAlex

Summary This study evaluated 56 documents developed by 11 nonprofit and public social service agencies to provide information to clients. The author used the Flesch Reading Ease, Simple Measure of Goobledegook (SMOG), and Gunning Fog Index formulas to assess reading grade levels and the Suitability Assessment of Material to evaluate overall suitability for readers with limited literacy skills. Findings All documents but one were above the recommended fifth grade level for low-literacy materials. Suitability Assessment of Material scores indicated 44.6% ( n = 26) were not appropriately formatted for readers with limited literacy skills. Applications Findings suggest a need for improving social service agencies’ and practitioners’ knowledge and awareness of the importance of assessing the readability and suitability of print materials, especially those intended for clients.

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)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.302
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2018
Admission routes1
Has abstractyes

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