MétaCan
Menu
Back to cohort

From Telegraphs to Telephones: Tracing the Transition in Telephony

2025· article· en· W4416006460 on OpenAlexaffabout
David Foord

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsHistoriographyNewspaperPerspective (graphical)NarrativePhoneTransition (genetics)PoliticsGovernment (linguistics)

Abstract

fetched live from OpenAlex

This paper contributes to the historiography of telegraphs and telephones along with research on the multi-level perspective on socio-technical transitions. To contribute to these literatures, we examine the question of how Canada’s political, economic and social circumstances and dynamics shaped its history and transition from telegraph to the telephone industries. In our social science, narrative history, we employ a dual integrity model, taking a Janus perspective in using new archival materials on both telegraph and telephone systems to contribute to the historiographical debate as well as testing and refining the multilevel perspective on socio-technical transitions. The paper contributes to the transition literature by examining a new historical transition case within a lesser studied system in this field, that of telecommunications. We examine government initiatives, public policies, firm-level operations and marketing and changes in user practices behind the transition from telegraph and telephone systems in Canada. Our analysis of annual growth in infrastructure (number of poles, telegraph offices and telephones), usage (number of telegrams sent and telephone calls), telephone company advertising in Canadian newspapers (for business, social and others uses) and firm-level revenue contributes new insights to political economy and social history explanations of the transition.

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0050.005
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.008
GPT teacher head0.240
Teacher spread0.232 · 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
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicICT Impact and PoliciesFrench-language works237,207