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Record W4242959105 · doi:10.32920/ryerson.14658084

An Analysis of the Media’s Role in the 2008 Economic Recession

2021· preprint· en· W4242959105 on OpenAlexaff
Sadia Kamran

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRecessionCritical discourse analysisDominance (genetics)ConversationBankruptcyContext (archaeology)Financial crisisPoliticsPolitical economyPerceptionPower (physics)Framing (construction)Political scienceSociologyEconomicsKeynesian economicsIdeologyPsychologyLawHistory

Abstract

fetched live from OpenAlex

The purpose of this Major Research Paper (MRP) is to explore the 2008 economic recession and the unprecedented collapse of the American economy triggered by the mortgage market that affected individuals and corporations. One of the objectives of this work is to identify the key actors who prompted the economic crisis and how they influenced the public perception of investing in the housing that led to bankruptcy for millions. Another objective is to identify the media’s role in the recession and some of the key lessons learned in how they could have mitigated the crisis. This MRP will undertake a critical discourse analysis built on the seminal work of theorists (e.g., Van Dijk (1977), and Fairclough (1985) to analyze media communications during the recession. Critical discourse analysis would be used as a theory given it examines the interaction between the abuse of social power, dominance and inequality perpetuated by institutions through text and conversation in the social and political context (Wodok and Myers, 2001).

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)0.003
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0060.007
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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
Published2021
Admission routes1
Has abstractyes

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