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Record W2021274490 · doi:10.5539/ies.v3n4p2

A Decade of Rural Research: What have We Learnt about Adult Language, Literacy and Numeracy?

2010· article· en· W2021274490 on OpenAlexvenueno aff
Chris Atkin

Bibliographic record

VenueInternational Education Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsNumeracyLiteracyRural areaCurriculumWorkforceEconomic growthPopulationPedagogyMiddle classSociologyPsychologyMathematics educationPublic relationsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The role of functional literacy, linked to employment, leads to a narrow view of rural learners' need both economically and socially. The drive for individuals to take responsibility for their own learning and development is, indeed, a good thing. However, the burden of guilt felt by those who are unable, or unwilling, to achieve the standards set out in the Skills for Life (DfEE, 2001) strategy, is significant. This deficit model of applied functionality is likely to result in a fracturing of traditional social networks upon which much of rural life is constructed, leading to social fragility. The changing character of the English countryside with its rising population drawn from urban and international migration is striking and certainly challenges the caricature of a white, male, middle-class countryside. With these changes comes a demand for an alternative curriculum which reflects the large number of older learners and the language, literacy and numeracy (LLN) needs of both an established labour market and a new international workforce.

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)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.011
Scholarly communication0.0090.013
Open science0.0010.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.100
GPT teacher head0.543
Teacher spread0.444 · 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 designQualitative
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
Published2010
Admission routes1
Has abstractyes

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