MétaCan
Menu
Back to cohort
Record W2979154306

PARTIES AT THE WATER’S EDGE: CANADA’S POLITICAL PARTIES AND THE FOREIGN POLICY DOMAIN

2019· dissertation· en· W2979154306 on OpenAlexaboutno aff
Cassandra Preece

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsForeign policyPolitical scienceDomain (mathematical analysis)Enhanced Data Rates for GSM EvolutionPolitical economyPublic administrationLawSociologyComputer scienceTelecommunicationsMathematics
DOInot available

Abstract

fetched live from OpenAlex

Foreign policy is the nexus between domestic and international political systems. Studies in Canada have so far produced mixed findings related to the role of political parties in foreign policy. Drawing from campaign promise, issue ownership and foreign policy decision-making literature, this dissertation investigates whether there is a foreign policy domain consistently dominated by a particular political party in the Canadian context. Part I uses data from the Comparative Manifesto Project (CMP) combined with manually coded foreign policy promises to determine the content and scope of foreign policy-related election promises in Canada. Part II follows the well-established pledge approach to measure promise fulfilment of foreign policy promises of Canadian governing parties following elections. This dissertation not only seeks to determine whether parties matter in the context of foreign policy, but also whether one party consistently “owns” the foreign policy domain or specific foreign policy issues. Findings from this research will fill an existing gap in the literature related to policy-specific promise fulfillment in Canada and will bridge existing theoretical assumptions related to political party behaviour and foreign policy decision-making.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.101
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0180.006
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
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 head0.009
GPT teacher head0.196
Teacher spread0.188 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMacSphere (McMaster University)Same topicCanadian Identity and HistoryFrench-language works237,207