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Record W3150564233 · doi:10.29173/iasl7555

Integrating a Community Library into the Teaching and Learning Programme of Local Schools

2021· article· en· W3150564233 on OpenAlexvenueno aff
M. Eddy Maepa, Rhandzu Mhinga

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmOutreachSociologySchool libraryLearning communityService (business)Value (mathematics)Resistance (ecology)PedagogyMathematics educationLibrary sciencePublic relationsPsychologyPolitical scienceBusinessComputer scienceMarketing

Abstract

fetched live from OpenAlex

According to estimates by Statistics South Africa, only 33% of learners in the Limpopo Province (one of the nine Provinces in South Africa) have access to a functional school library or media centre. This has been regarded as one of the main factors which have contributed to the Province consistently producing one of the lowest pass rates in comparison to its counterparts. While there was enthusiasm amongst some teachers that the establishment of Seshego Community Library would bring some relief to educators starved of a functional library service in their schools, some teachers and learners were not as enthusiastic and receptive to the Community Library. This paper explores some of the barriers inherent in introducing a library to a community which was not previously exposed to, and accustomed to making use of its services, and making it an integral part of the teaching and learning programme. Issues of resistance to the community library’s outreach programme, largely emanating from lack of motivation and a low morale amongst some teachers and principals alike, as well as an erosion in the culture of teaching and learning, are explored. There is a need to break down the existing barriers to encourage teachers and learners to make use of the Community Library’s services and facilities to add value to their teaching and learning endeavours.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.013
Open science0.0000.000
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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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