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Constructing Campus Cultural Values and Promoting Soft Power of University

2014· article· en· W1863740980 on OpenAlexvenueno aff
Yongyou Wang

Bibliographic record

VenueCanadian social science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
Fundersnot available
KeywordsSoft powerHonorPower (physics)SociologyFaithSoulMarxist philosophyPatriotismHard powerSoft drinkIdeal (ethics)Cultural valuesMedia studiesEnvironmental ethicsSocial scienceLawTheologyPolitical sciencePhilosophyComputer science

Abstract

fetched live from OpenAlex

Campus cultural values, is soul of soft power of university. Cultivating, compacting and constructing campus cultural values are essential requirements for promoting soft power, consolidating Marxist guiding status and forming teachers and students’ common ideal faith, strengthening their patriotism education and forming their common goal purist, and carrying out the education of socialist outlook for honor and dishonor and forming campus civilized new trend. The soft power of university is promoted by deeply excavating and researching historical and cultural remains of university, systematically summarizing and compacting historical and cultural traditions, and energetically inheriting and developing great culture of university. Furthermore, cultural environment including “soft”, “hard”, “virtual” and “realistic” environment that are run through campus cultural values should be powerful built.

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)0.002
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.013
Scholarly communication0.0150.005
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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
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

Citations1
Published2014
Admission routes1
Has abstractyes

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