Sustainability: Panacea or Local Energy Injustice? A Qualitative Media Review of Newfoundland and Labrador’s Wind-to-Hydrogen Boom
Bibliographic record
Abstract
Despite vast wind energy potential, the Canadian province of Newfoundland and Labrador (NL) has historically lagged in installed capacity due to socioeconomic and technical barriers. The emergence of hydrogen as an alternative energy carrier has transformed prospects for a wind industry on the island, allowing for the possibility of exports. Since the lifting of a provincial wind energy moratorium in 2022, several companies have proposed more than 25 gigawatts (GW) of wind-to-hydrogen (W2H) capacity. Proponents and opponents differ considerably in their view on whether W2H projects will advance provincial sustainability—a debate which can be further understood through energy justice analysis. Given the current lack of empirical evidence, the study adopts a systematic review of media reports pertaining to six leading W2H projects in the province. Basic descriptive statistics (means, frequencies, etc.) are used to describe the metadata and preliminary coding process. Deductive and inductive thematic analysis are then applied to the complete dataset of online news articles (n = 112) with the support of a qualitative data management software (NVivo, Version 14). The findings build upon, challenge, and make novel contributions to several tenets of energy justice. From a distributive justice perspective, temporal variations in employment, centralization of resource revenues, and the anthropocentric nature of defined risks are highlighted. From a procedural justice perspective, social acceptance of projects, as well as the shortcomings of environmental impact assessment, are elaborated. From a recognition justice perspective, the paper demonstrates Indigenous involvement in W2H governance, yet demands an interrogation of intra- and intercommunity diversity. From a cosmopolitan justice perspective, the paper finds weak evidence of supporting vulnerable global populations through decarbonization, yet some prospects through enhancing energy security for importing countries. With respect to media reporting, the findings illustrate the outsized role of independent media in advancing evidence-based justice discourses and the central function of public media in covering rural natural resource developments. Ultimately, this study urges policymakers and private developers to ensure fair benefit distribution, deep participation, and inclusion of diverse communities during the formative stages of the W2H industry in NL and beyond.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".