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Record W3136998682

Climbing Parliament’s Hill: Examining the Lack of Gender Parity Within Canadian Parliament

2019· dissertation· en· W3136998682 on OpenAlexaboutno aff
Avninder Rakhra

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsParliamentParity (physics)Political scienceClimbingLawGeographyPhysicsPolitics
DOInot available

Abstract

fetched live from OpenAlex

The goal of this thesis is to examine the question: why the current 42nd Parliament of Canada fails to achieve gender parity within the House of Commons? Additionally, it assists in comprehending why Canada’s Parliament does not have a substantial number of female Members of Parliament (MPs). The paper also looks at the low number of women candidates in the 2015 election in comparison to the number of male candidates. I also study the contributing factors hindering the progress of parity. My initial hypothesis is that the lack of gender parity in the House of Commons is due to the political process, which includes the role of political parties, the electoral system, the lifestyle of MPs and the role of the media. I also hypothesize that it is due to incumbency and the lack of priority given to achieving gender parity. Thus, with a lack of priority and more male candidates, achieving gender parity is more difficult. This also includes the lack of willingness on the part of certain leaders and parities.\nWhile certain scholars have studied components of gender parity, I believe there is a gap in the literature. Furthermore, the vast majority of scholarship tends to focus on one specific component of gender parity and not the various components together. The literature also does not delve deep enough into the issue and for this reason I hope to add to the existing literature. Subsequently, this may further assist in helping close the gap. \nWithin the thesis, I employ various research methods. One of the research methods is the use of both primary sources and secondary academic studies. This includes both Canadian and non-Canadian sources which are then applied to my arguments. Another method is the conducting of interviews with current and former MPs. I also look at newspaper articles, government databases and websites, bills presented by MPs and public speeches/statements.\nAfter conducting my research, I find a number of factors contributing to the lack of gender parity in Parliament. I also examine the various regional patterns of female candidacy within in Canada, prior to presenting my findings. I find that one of the factors contributing to the lack of gender parity is due to the role and responsibility of political parties and leaders. Another factor is the electoral system. Other factors include the role of the media and the profession itself. I also examine a number of potential solutions that can assist in achieving gender parity, although I do not endorse any one particular remedy. These include quotas, electoral reform, the appointment and promotion of women within parties, making Parliament more “women friendly” or “family friendly”, role models and mentoring, financial penalties and incentives, and running women in more “winnable ridings”. In conclusion, after researching and examining these factors, my findings reveal that my initial hypothesize was only partly correct and did not go far enough. Furthermore, my initial hypothesis did not include potential solutions for gender inequality. On a personal level, I find the role of political parties and leaders the most convincing.

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)0.009
metaresearch head score (Gemma)0.034
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.008
Science and technology studies0.0240.008
Scholarly communication0.0080.003
Open science0.0040.005
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 head0.115
GPT teacher head0.328
Teacher spread0.213 · 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
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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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