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Record W2144108461 · doi:10.22230/cjc.2008v33n1a1865

Biotechnology, the Environment, and Alternative Media in Malaysia

2008· article· en· W2144108461 on OpenAlexaffvenue
Sandra Smeltzer

Bibliographic record

VenueCanadian Journal of Communication · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsWestern University
Fundersnot available
KeywordsGovernment (linguistics)MainstreamHegemonyScarcityState (computer science)Political scienceBusinessPublic relationsEconomicsLawPoliticsMarket economy

Abstract

fetched live from OpenAlex

The Malaysian government has embarked on an ambitious path to make biotechnology a key driver of the country’s economic future. This burgeoning sector is being developed by a state with a problematic environmental track record, which does not bode well for the future. As mainstream Malaysian media are heavily controlled through a range of restrictive laws and hegemonic pressures to self-censor, critical coverage of biotechnology and its implicit ties to the environment is, not surprisingly, sparse. The focus of this article, however, is the relative scarcity of critical discussions about these issues in the country’s vital alternative media. This article offers a number of suggestions for this shortfall, including government restrictions on available information, the complexity of relevant issues, a lack of recognition of the industry’s importance, and the tenuous relationship between environmental NGOs and alternative media practitioners and organizations.

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)0.002
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.005
Scholarly communication0.0090.006
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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

Citations6
Published2008
Admission routes2
Has abstractyes

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