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Record W2888115568

Learning About Oneself: An Essential Process to Confront Social Media Propaganda Against the Resettlement of Syrian Refugees

2017· dissertation· en· W2888115568 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2017
Typedissertation
Languageen
FieldPsychology
TopicCognitive and psychological constructs research
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeSnowball samplingContext (archaeology)Political scienceSocial mediaInclusion (mineral)Citizen journalismQualitative researchPublic relationsSociologyPsychologySocial psychologySocial scienceGeographyMedicineLaw
DOInot available

Abstract

fetched live from OpenAlex

Research Problem: 
\nPublic reaction to the 2015-2016 resettlement of Syrian refugees to Canada ranged from strong support to active resentment. This study explored some of those reactions: those of host society youth. It examined the process of this youth learning about themselves in the context of the social media propaganda about the resettlement of Syrian refugees, and investigated how the public opinion about the refugee resettlement affected their perception of their roles in the integration and inclusion of these newcomers. 
\nResearch questions: 
\n1.How do youth construe online interactions about the Syrian refugee crisis?
\n2.How do youth construe their role in the integration and the inclusion of refugees in a context where the image of refugees is deeply influenced by social media?
\n3.What knowledge and skills do youth develop when they engage in analyzing their thoughts and behaviours in regards to sensitive and controversial issues such as the refugee crisis and resettlement?
\n4.How could this knowledge and these skills facilitate their engagement in civic online reasoning and participatory politics?
\nMethodology: 
\nThe researcher conducted more than 160 hours of qualitative in-depth interviews with 42 host society youth between 18 and 24 years old from North America, Europe and the Middle East. For the purpose of this thesis, only data collected from the Canadian participants was analyzed and shared. The participants were recruited through a snowball sampling. They were active on social media, supportive of the Syrian refugee resettlement in Canada, but deliberately acting as passive bystanders whenever they encountered online posts and interactions about the Syrian refugee crisis. Adapting four techniques from George Kelly’s Personal Construct Psychology (Kelly’s self-characterization technique, Procter’s Perceiver Element Grid, Kelly’s Repertory Grid Test and Hinkle’s laddering technique), data collection included three to four interviews with each participant. The interviews provided the participants with opportunities to delve into their own construct systems and to reflect on the genesis of their constructs. 
\nResults and Conclusions: 
\nBy reflecting on their own behaviours online, participants realized that they could control how social media influenced them, and shape the online image of the Syrian refugees in host countries. While their empathy towards refugees increased, participants identified factors that could lead to Islamophobia, racism and fear, and developed strategies to counterbalance them online. The process of learning about themselves was key to transform the participants from passive bystanders into active agents of change, ready to confront digital propaganda.
\nCivic educators, social workers, curriculum developers, policy makers and parents concerned with the takeover of social media by hate speech proponents can apply these findings and help youth withstand manipulation and fight racism, hate speech, radicalization, and cyberbullying through the Get Ready to Act Against Social Media Propaganda model generated by this study. The model includes five iterative stages: Question, analyze, design, prepare and evaluate.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.387
Teacher spread0.338 · 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