Framing Huawei: from the target of national debate to the site of international conflict in Canada’s mainstream online newspaper
Bibliographic record
Abstract
Abstract Purpose This study was conducted to investigate the Canadian mainstream online media report of Huawei, the Chinese IT company and critical actor in China’s OFDI attempt, and how the media deviate or conform to the Government’s and the social and political elites’ position(s). Design/methodology/approach Content analysis and discourse analysis were performed to analyse the news articles from The Globe and Mail concerning Huawei from the beginning of 2018 to March 2019. Public opinions, represented by the Nanos polls available from the news articles were also analysed. Findings We found that Huawei was mainly framed as national security threat vs valued partner in the national debate whether to allow Huawei to contribute to Canada’s 5G construction before the arrest of Meng Wanzhou, and the centre of the Sino-West conflict after the critical incident. The Globe and Mail tried to index multiple sources, while sticking to the long-formed schema about China and Chinese enterprises, which has a deep effect on the public opinions. The journalists rose to be the predominant source of the news report and seemed to be acting on their own after the critical incident, showing an event-driven tendency. Practical implications It helps the readers to understand the bias embedded in media report in its political contexts. Journalists should take caution because they could reenforce the same schema even though efforts have been made to maintain media’s democratic façade. Social implications It shows that MNCs and international media have a much closer relationship than we expect. The media in the western world could make or break a MNC’s prospect in a country. Originality/value It contributes to the contextualization of such media theories as indexing hypothesis and cascading activation model. In an era of anti-globalization and media war, such theories need to be re-examined especially when it comes to the report about foreign affairs concerning a country and its MNCs from a different ideological camp.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".