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Record W2968623374 · doi:10.3968/11127

Exploration on the Backbone Training System of College Students in Ideological Propaganda Work in the New Media Age

2019· article· en· W2968623374 on OpenAlexvenueno aff
Lujiang Zhou, Zhi Dai

Bibliographic record

VenueCanadian social science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyWork (physics)Core (optical fiber)Position (finance)SociologyPublic relationsPolitical scienceManagementPedagogyLawEngineeringPoliticsBusiness

Abstract

fetched live from OpenAlex

It is of great strategic significance to cultivate the backbone of college students in propaganda work in the new media era to enhance the education of socialist core values and consolidate the ideological position of colleges and universities. Based on the operation system of ideological propaganda team and the career model of student backbone in colleges and universities, this paper explained a “T” type training system of core students in ideological propaganda work in colleges and universities, which provided scientific theoretical guidance for the selection, cultivation and management of student leaders group. In view of the actual work of student backbone group in ideological propaganda work, based on the Kirkpatrick evaluation model, the evaluation model of student cadre training effect in ideological propaganda work in colleges and universities was constructed, with a view to realizing systematic, standardized and scientific training feedback mechanism.

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)0.004
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.336
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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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