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Record W2973526618 · doi:10.29173/iasl7720

Culturally-sensitive learning practices

2021· book-chapter· en· W2973526618 on OpenAlexvenueno aff
Lesley S. J. Farmer

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typebook-chapter
Languageen
FieldComputer Science
TopicEducational Challenges and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsHofstede's cultural dimensions theoryCultural learningCultural diversityPedagogyCultural competenceCulturally appropriateSociologyKnowledge managementPublic relationsPsychologySocial psychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

In today’s global world, to provide meaningful education, teacher-librarians and their students need to become culturally competent: open to learning about other cultures and sharing one’s own culture, able to change personal perspectives, and able to communicate effectively across cultures. Hofstede’s model of cultural dimensions provides a framework for examining culturally-sensitive library implications. Specific strategies are suggested to address language barriers, student-teacher relations, choosing resources, learning activities, technical issues, and assessment.

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)0.016
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.034
Scholarly communication0.0120.010
Open science0.0030.022
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.002

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 head0.066
GPT teacher head0.305
Teacher spread0.239 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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