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Record W2990023956 · doi:10.5539/ies.v12n12p85

Johan Vilhelm Snellman’s–Finnish Philosopher, Writer, Diplomat–Statement “Science Centers for All”

2019· article· en· W2990023956 on OpenAlexvenueno aff
Abdullah Aydın

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsSoulStatement (logic)Theme (computing)GermanVirtueScope (computer science)Political scienceSocial scienceSociologyLawHistoryEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

“Go to temples of science and ideas of Europe. Imitate the Tugendbund, ‘the Union of Virtue’, of which thousands of German youth are the members. Always keep the rule of ‘Fit soul is in fit body’ in mind” (Petrov, 2013, p. 72). This study aimed to show the similarities, in terms of expression, emphasis, and implication, in the about/mission/vision/goals/objectives of various science centers from around the world and in the basic themes derived from Snellman’s statement above, namely, Science for all, Science Centers for all, and Human welfare that he made as a challenge to not only his people but to everyone. Document and content analyses were applied in the study. Within the scope of these analyses, this study investigated the about/mission/vision/goals/objectives sections of websites of science centers from around the world (Asia, Europe, Global, Latin America/The Caribbean, North America, Africa). From this investigation, similar basic themes, derived from Snellman’s statement challenging his people/everyone to adopt this devotion to science, were found in the areas of i) expression in ASTC, CIMUSET/CSTM, CASC and SAASTEC; ii) emphasis in ECSITE, ASDC, ASCN and NSCF; and iii) implication in ASPAC, ASTEN, NCSM, ABCMC and Red-POP. These basic themes, as found in the about/mission/vision/goals/objectives of science centers, can, in effect, be narrowed down to the one theme of “cultural institutions will be a big part of human life” (Madsen 2017, p. 68) science centers in the global village (Touraine, 2016, p. 121) of the future.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.767
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.124
GPT teacher head0.398
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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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