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Record W4402240069 · doi:10.62320/jfbr.v3i2.51

Do exporters of Canadian forest products price to market?

2024· article· en· W4402240069 on OpenAlex
Kurt Niquidet, Kyle Sia-Chan, Jonathan Kan, Lili Sun, Craig Johnston

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Forest Business Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsBank of CanadaCanadian Sport Centre PacificNatural Resources CanadaBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsBusinessCommerceInternational trade

Abstract

fetched live from OpenAlex

Forest products in Canada contribute significantly to the Canadian trade balance. Canadian producers depend heavily on export markets raising the question: how do exchange rate fluctuations impact Canada’s competitiveness in foreign markets? The paper applies a fixed-effects model with individual slopes to investigate this question. Twenty years of monthly data are employed to study the pricing-to-market (PTM) behaviour of Canadian softwood log, lumber and pulp exports as the exchange rate changes. We find a great degree of incomplete exchange rate pass-through, with PTM being apparent for Canadian exporters, particularly in major markets. The export price adjustment tends to mitigate the effect of exchange rate fluctuations on foreign currency prices of Canadian products in most cases. This pricing behaviour reflects exporters’ desire to stabilize their share of the destination market.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.320
Teacher spread0.273 · 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