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Record W4220753676 · doi:10.1108/jhrm-09-2021-0050

Stelco, Sears Canada and CN Rail: archival sources of advertising and marketing history in the Library and Archives Canada collection

2022· article· en· W4220753676 on OpenAlexaffabout
Dalton Campbell, Kelly Anne Griffin, Andrew Elliott

Bibliographic record

VenueJournal of Historical Research in Marketing · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAmerican History and Culture
Canadian institutionsLibrary and Archives Canada
Fundersnot available
KeywordsPublicityNational archivesOriginalityAdvertisingBusiness historyLibrary scienceBusinessPolitical scienceMarketingHistoryLawComputer scienceArchaeology

Abstract

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Purpose The archival records of Canadian corporations held by Library and Archives Canada (LAC) are a rich source of primary documents for the study of the history of marketing and advertising in Canada. The paper discusses the records of iconic department store Sears Canada, steel manufacturer Stelco, and Canadian National, the country’s largest railway, provide primary source material on marketing, sales, catalogues, promotions, celebrity endorsements, sponsorship of charitable causes and other areas of publicity. Additionally, discussing archival records provides a case study of the major archival processes involved in making historical documents available to researchers and the general public, including appraisal and evaluation, archival processing, preservation and digitisation. Design/methodology/approach The paper discusses and highlights primary source archival records for the study of marketing history. These archival fonds are unique primary source records that document three historically significant Canadian corporations and their roles in Canadian history. Findings The archival records of Canadian corporations held by Library and Archives Canada (LAC) are a rich source of primary documents for the study of the history of marketing and advertising in Canada. The records of iconic department store Sears Canada, steel manufacturer Stelco, and Canadian National, the country’s largest railway, provide primary source material on marketing, sales, catalogues, promotions, celebrity endorsements, sponsorship of charitable causes and other areas of publicity. Additionally, discussing archival records provides a case study of the major archival processes involved in making historical documents available to researchers and the general public, including appraisal and evaluation, archival processing, preservation and digitisation. Originality/value The archival records of Canadian corporations held by Library and Archives Canada (LAC) are a rich source of primary documents for the study of the history of marketing and advertising in Canada. The records of iconic department store Sears Canada, steel manufacturer Stelco, and Canadian National, the country’s largest railway, provide primary source material on marketing, sales, catalogues, promotions, celebrity endorsements, sponsorship of charitable causes and other areas of publicity. Additionally, discussing archival records provides a case study of the major archival processes involved in making historical documents available to researchers and the general public, including appraisal and evaluation, archival processing, preservation and digitisation.

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)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.136
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0280.073
Science and technology studies0.0250.006
Scholarly communication0.0190.004
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.018
GPT teacher head0.212
Teacher spread0.194 · 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 designNot applicable
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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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