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Record W7095936749

(120)-- Reports- Descriptive (141) Speeches/Conference Papers (150)

2016· article· en· W7095936749 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsBroadcasting (networking)Government (linguistics)CorporationRadio broadcastingPublic broadcastingCommercial broadcastingBroadcast journalismPrint media
DOInot available

Abstract

fetched live from OpenAlex

Arguing that the acceptance of educational technology in Quebec is influenced by issues of economic survival and cultural identity, this paper discusses educational technology in terms of three types of media--computers, broadcast media (radio and television), and print media. Selected educational operating systems are also discussed. A search of the ERIC database is cited to show that, of these media, television has received the most attention from Canadian researchers in the past 7 years. It is noted that: (1) political, economic, and cultural considerations have played a role in broadcasting in Canada; (2) the federally sponsored Canadian Broadcasting Corporation has evolved as a two language system on both radio and television; and (3) the Quebec government also supports Radio Quebec on radio and television. It is concluded that educational technology and greater communications among all concerned about education and community development may evolve new paths of education and national identity, building on what is, what was, and what might be. (12 references) (DB) Reproductions supplied by EDRS are the best that can be made from the oiliginal document.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.553
Threshold uncertainty score0.789

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4470.296

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 head0.053
GPT teacher head0.232
Teacher spread0.179 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

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Same topicLiteracy, Media, and EducationFrench-language works237,207