This budworm's for you: how framing, trust and participation affect attitudes on natural resource management issues in Atlantic Canada and New England
Bibliographic record
Abstract
Forest management is a policy issue that is value-laden, and evokes controversy.This is especially true in New Brunswick, a province of Canada that is heavily reliant on the forest industry for the economic health and well-being of its residents.This reliance shifts the balance of political power, by placing a large degree of decision-making power in the hands of private interests, who are able to influence the direction of policy even over the protests of the public.This dissertation aims to examine three separate, yet interrelated aspects of forest management in New Brunswick, with the purpose being to uncover how these relationships influence the political environment in New Brunswick, and how they affect issues of representation and democracy throughout the province.Specifically, it focuses on a naturally occurring insect outbreak that is currently threatening the region, the spruce budworm, and offers three separate chapters on individual levels of trust, media framing, and public involvement in decisionmaking.First, using an original public opinion survey, Chapter Two identifies the main determinants of levels of trust for the provincial government, scientists and academics, and the forest industry.Chapter Three then turns to a comparison of national and local news media, to assess whether the industry-owned local media offers a biased framing of forestry issues in their news articles, an accusation that has been laid against them several times over the last four iii decades.Chapter Four then turns to the issue of public involvement in decision-making regarding the management of the spruce budworm outbreak; a comparison is made between New Brunswick and Maine, USA, to identify how issue definition and related factors shape decisions on whether to include the public in decision-making, what form that takes, and why.Findings from these chapters inform the final discussion in Chapter Five, which identifies the themes of power, trust and control as the threads that bind together the issues of trust, media framing and public involvement.This conclusion suggests that the power the forest industry wields in forest management policy and implementation essentially removes the power citizens are meant to have in a representative democracy.Citizens are not unaware of this close relationship, and place their trust in scientists to help right the wrongs they see in forestry in the province; this is seen particularly among the citizens most vulnerable to shifts in the fortunes of the forest industry, who seem to identify science as the means through which they can gain stability.However, even scientists are constrained by the political and information environments in which they operate.Efforts to keep the public informed are constrained by the narrow presentation of forestry issues in the local media, which not only eliminate the media's role as watchdog, but also eliminates the media as a vital linkage institution, providing the information the public needs for keeping the major powers in society accountable.There is also the need for control that is inherent in the aspects of forest management presented here, even in the methods of public communication which have the potential to empower the public.In choosing a strategy of informing the public through one-way communications, scientists and administrators are maintaining control of the message, and the decision-making power within the program.This calls into question whether scientists, or anyone else within the province, have the capacity to place power back in the hands of the public.It appears that without a force powerful enough to iv dislodge the place of the forest industry in the policy process, citizens will continue to be disempowered and placated, and the province will continue to be held hostage by the forces of nature and the needs of those who try to tame them.v ACKNOWLEDGMENTS After close to a decade of graduate study, I would like to acknowledge those that have supported me along the way.A large debt is owed to my family, especially to my mother, who has been telling me for my entire life that no matter what, I am the smartest person in the room.I would also be remiss if I did not thank Dr. Brooke Ruxton for serving as inspiration to join her illustrious rank.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".