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Record W4402715155 · doi:10.1016/j.telpol.2024.102864

Technological literacy and employment: An inquiry into the adoption of learning technologies

2024· article· en· W4402715155 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

VenueTelecommunications Policy · 2024
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsWestern University
Fundersnot available
KeywordsLiteracyBusinessKnowledge managementSociologyPedagogyComputer science

Abstract

fetched live from OpenAlex

This study investigates the relationship between online learning activities for educational, professional, or personal purposes and employment likelihood using the Information and Communication Technology (ICT) Usage Survey conducted by the Turkish Statistical Institute (TSI) between 2015 and 2023. Utilizing a nationally representative survey, we analyze (1) online course enrollment and (2) online learning engagement (self-learning and communication-based learning activities) and their relationship with being employed. The results highlight that all forms of online learning—course enrollment, self-learning, and communication-based learning activities—positively influence employment. Regarding the magnitude of the effects, online learning engagement is as useful as online course enrollment, underscoring the importance of engagement that can supplement formal or structured learning methods. Furthermore, online learning activities benefit disadvantaged labor groups such as female and older workers more. The findings emphasize the potential of online learning activities to promote lifelong learning and mitigate barriers to employment, particularly among older individuals and women. Considering these dynamics, this study allows policymakers and practitioners to develop more effective strategies to address gender disparities and foster inclusive workforce participation. • Individuals engaging in online learning activities are more likely to be employed. • Online learning engagement is as useful as online course enrollment, underscoring the importance of communication via online tools and interactive learning experiences that can supplement formal or structured learning methods. • A significant portion of the observed rise in employment linked to online education can be attributed to increased participation in the labor force. • Online education shows greater benefits for older individuals, potentially mitigating age-related barriers to employment and promoting lifelong learning. • Online education has a stronger impact on women's employment, suggesting it can help address gender disparities in the job market by enhancing women's employment prospects.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.331
Teacher spread0.305 · 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