TUT 3

Agenda and context

• Instructor introduces session while coming off a flu; notes about reduced energy and physical distancing while moving around the room.
• Brief on alternate activities from last week: these are designed to be more challenging than tutorials and lectures.
• If you received a 0.5 mark earlier, feedback was provided to help demonstrate understanding of concepts (covariation model). The example shows that simply stating time management as a cause is not enough; needs appeal to the model’s components (consistency, consensus, distinctiveness).
• Offer to discuss unclear items one-on-one to clarify understanding.
• Today’s plan:
  • Start with the tutorial activity (≈ 15 minutes).
  • Present the final list of variables for your reports (18 variables total; more than 15 is common).
  • Develop hypotheses for each of the 18 variables (at least one hypothesis per variable).
  • Brief tips on independent research for the research report and the live survey.
  • Survey link is live and data collection begins; attention to eligibility and data collection logistics.

Covariation model and the alternative activity discussion

• Covariation (Kelley) model focuses on explaining behavior via three components:
  • Consistency: Does the behavior occur reliably over time?
  • Consensus: Do others behave similarly in the same situation?
  • Distinctiveness: Does the behavior occur across different contexts or is it specific to a particular target or situation?
• Example discussed in class: explaining a friend being late and disorganized to a social event.
  • If the behavior is consistent (high consistency), the attribution is more likely to be to the person (e.g., bad time management).
  • If many others are late (high consensus), attribution leans toward situational causes.
  • The instructor used these patterns to point out what constitutes a robust answer for the 1-mark drop from 0.5 to 1 mark (more than a couple of sentences per part).
• Reminder: If students are unsure why they scored 0.5 or want more help, they should see the instructor for guidance.

Misinformation activity

• Topic: misinformation and attitude change; misinformation is false or inaccurate information that can mislead and spread widely (e.g., discussions around COVID-19).
• Intervention: Bad Facts game (a game-based intervention designed by social psychology researchers) to expose manipulation tactics used to mislead about vaccinations, especially on social media.
• Students could choose roles: spread misinformation or fight misinformation.
• Access: QR code or URL to participate; the activity takes ≈ 15 minutes.
• Observations from the activity:
  • Fighting misinformation tends to be more effective than spreading it (in some cases).
  • Discussion points include the kinds of misinformation that circulate (e.g., 5G claims, vaccine-autism connections).
  • Notable impact of language features: emotive language, use of credentials (e.g., PhD/MD) to mislead.
  • AI-generated content is increasingly hard to spot; learning to detect AI-generated misinformation is important.
• Discussion prompts: how misinformation spreads in the modern social-media environment; the role of engagement metrics (comments, controversy) in increasing post reach.
• The instructor connected misinformation to broader skills: improving ability to recognize manipulative language and sources; AI-awareness as a necessary literacy skill.

Misinformation discussion and personal reflections

• Students shared examples of misinformation (e.g., vaccine concerns, general conspiracy claims).
• The instructor highlighted ethical considerations and practical implications for health communication.

Research report overview and context

• Topic: psychological correlates of organizational deviance (organizational deviance being the dependent variable).
• Prior work (two weeks ago): brainstormed a broad list of potential independent variables that might correlate with organizational deviance.
• This week’s focus: review the variables chosen for the survey, and formulate hypotheses for each variable.
• Rationale for variable selection:
  • A large pool of suggestions (≥70 suggestions across the cohort) was condensed to 18 variables to keep the survey manageable and to ensure feasible literature support.
  • Some ideas were discarded because they were hard to measure, lacked sufficient literature, or were not easy to implement.
  • The chosen variables balance relevance to organizational deviance, ease of measurement, and availability of theoretical support.
• Key reminder: the exercise links each variable to the dependent variable (organizational deviance) and clarifies how the variable is operationalized in real-world settings.
• Clear emphasis on critical thinking and theoretical grounding for hypotheses rather than purely statistical considerations.

The 18 variables for the survey (measurement details, expected relations, and notes)

• Note: The transcript lists 18 variables on the board; several have explicit item counts and scales. Some labels appear with typos or are described in phrases rather than as fixed titles. The notes below reflect the content as presented and indicate where details are explicit vs. inferred from contextual description.

1) Job satisfaction

• Items: 5 items
• Scale: 1 to 5 (strongly disagree to strongly agree)
• Typical expectation: Higher job satisfaction is associated with lower organizational deviance (i.e., less deviant behavior).
• Notes: Self-reported satisfaction with the current job.

2) Workplace belonging

• Items: 4 items
• Scale: 1 to 5
• Expected relation: Greater belonging relates to lower deviance; higher connection to the work group.

3) Workplace friendships

• Items: 6 items
• Scale: 1 to 5; includes reverse-scored items (lead score ordering may be inverted)
• Expected relation: More workplace friendships may reduce deviance due to social integration, but reverse items require careful coding in the method.

4) Pay equity

• Items: 3 items
• Scale: 1 to 5 (or similar Likert-type scale as described in slides)
• Expected relation: Higher perceived pay equity should relate to lower deviance (more fairness in compensation).

5) Job security

• Items: multiple items with some reverse items
• Scale: Likely 1 to 5 (typical Likert scale; specifics not stated in transcript)
• Expected relation: Higher job security -> lower deviance.
• Notes: There are reverse-scored items affecting scoring.

6) Leader–Member Exchange (LMX) / Leo member exchange

• Items: Focus on the relationship with supervisor; items include perceptions of supervisor as a person and knowledge/competence on the job
• Scale details: Not explicitly item-counted in transcript
• Expected relation: Higher quality LMX linked to lower deviance (better supervisor relationship reduces deviance).

7) Person–organization fit

• Item example: “The things that I value in life are very similar to things that my organization values.”
• Scale: Not explicitly given; treated as a multi-item measure in the slide
• Expected relation: Higher fit associated with lower deviance (values alignment reduces deviant behavior).

8) Organizational justice

• Concept: Fairness of treatment by organization
• Scale: Not specified in transcript
• Expected relation: Higher perceived justice linked to lower deviance.

9) Perceived organizational support

• Concept: Extent to which employees feel supported by the organization
• Scale: Not specified in transcript
• Expected relation: Higher perceived support linked to lower deviance.

10) Conscientiousness

• Items: Single overall score (one-dimensional trait)
• Scale: 1 to 9
• Expected relation: Higher conscientiousness linked to lower deviance (more self-discipline and rule-following).

11) Grieveliness (likely a mislabel for Agreeableness-related trait)

• Description: In the discussion, higher agreeableness (cooperative, kind, warm, sympathetic) is linked to lower deviance.
• Scale: Not specified; treated as a personality facet.
• Expected relation: Higher agreeableness -> lower deviance.

12) Machiavellianism

• Item: “I tend to manipulate others to get my way.”
• Scale: Not specified; typical measure would be multi-item scale for Machiavellianism
• Expected relation: Higher Machiavellianism related to higher deviance (more manipulative behavior).

13) Individual independence / Independent orientation

• Description: “If you’re more independent, you often do things on your own.”
• Scale: Not specified; treated as a personality/behavioral orientation
• Expected relation: Varied; independence could relate to deviance in complex ways depending on context.

14) Collectivism

• Description: Orientation toward group goals and cooperation
• Scale: Not specified
• Expected relation: Higher collectivism may be associated with lower deviance if deviance harms group functioning; context-dependent.

15) Subteam / Subsystem (described as the dependent variable in the slide)

• Description: This is treated as the dependent variable for regression/analysis—i.e., organizational deviance,
  including behaviors like lateness, shirking, or other deviant work behaviors (as implied by examples in the transcript).
• Notes: Examples given include “slacking at work” or “coming late to meetings” (paraphrased from the lecture).

16) Stress (implied variable for exploration)

• Notes: Mentioned in guidance about linking variables to deviance and as a possible correlate.

17) Burnout (implied variable for exploration)

• Notes: Mentioned alongside stress as a potential correlate; not detailed in item counts.

18) Additional variable(s) not explicitly named in transcript

• Notes: The slide was described as containing 18 variables; the transcript provided explicit names for many but not all; one or more variables were not named in the excerpt. The notes above capture the named ones and indicate where details were not specified in the transcript.

Measurement considerations mentioned in the transcript across variables

• Some scales include reverse-scored items (e.g., workplace friendships, job security).
• For reporting in the method section, explicitly state how many items were reverse scored and how the total/average scores were computed.
• Scales used include: Likert-type scales with ranges like 1-5 or a broader scale like 1-9 (as with Conscientiousness).
• The dependent variable (Subteam/organizational deviance) is described qualitatively via examples (e.g., lateness, underperformance); the exact operationalization will be detailed in the method.

How hypotheses will be developed for the 18 variables

• For each variable, generate at least one hypothesis about its relationship with organizational deviance (the dependent variable).
• Consider both direct and indirect pathways and potential boundary conditions (e.g., role of organizational culture, sense of belonging).
• Emphasize theory-based reasoning rather than purely descriptive expectations.
• Remember: the presentation emphasizes that there is no single right way to pick the two most interesting variables; you can pick any two that you find compelling or that link to broader theory (e.g., stress and burnout as related constructs).

Independent research and literature strategy

• Use Google Scholar in conjunction with the university library to locate peer-reviewed sources (chapters, articles).
• Two base papers recommended to start with (as foundational references):
  • "My Review of Workplace Deviance" (core paper)
  • "Deviance More Broadly" (foundational deviance literature)
• You are free to cite these sources in your report as starting points.
• Expect to cite a minimum of 10 resources; aim for more.
• Research process notes:
  • Literature review is iterative; start with core sources and then expand by citing papers that have cited the core sources.
  • Identify relevant theories and concepts to explain hypothesized relationships (e.g., belonging, organizational culture, sense of justice).
  • Collect and manage references with a reference manager (e.g., EndNote, Zotero).
• Search strategies: use keyword combinations such as "stress and workplace deviance," "workplace fatigue and deviance," and related terms; consider broad vs. narrow searches to capture occupational vs. general fatigue.
• Also consider papers that cite the core sources to discover by-paths and related theories.

Data collection and survey logistics

• Data collection link is live (via Blackbaud); QR codes are available for convenience, but a direct link is acceptable.
• All participants must complete the survey, and you should encourage peers to participate to maximize sample size.
• Key eligibility criteria:
  • Participants must be 18+ years old or university students aged 17+.
  • The survey focuses on workplace experiences; participants should have some work experience.
  • Retired individuals can participate if they have prior/work experience relevant to the workplace context.
• Students can test the survey themselves to experience the process; if you test, report that you are a psych 20 student to exclude your own responses from data.
• A PDF version of the survey is typically downloadable for review; if not available, review the online version.
• The survey window closes in two weeks (the announcement mentions close in two weeks on September 7). Plan accordingly.
• After the survey closes, the teaching team will download and analyze results and release them later; use the results to inform your two chosen variables and hypotheses.

Practical guidance for writing the report and using course materials

• The assessment materials are located under the Assessment tab (Blackboard/Altro), specifically for the Research Report, alongside the marketing criteria used for marking.
• Weekly slides contain crucial operational details (e.g., which items are reverse-scored, the exact scale ranges) and should be downloaded and consulted for accurately describing methods.
• The two core foundational papers should be used as citations to ground your arguments; additional articles should be sought to support each hypothesis.
• General advice for reading articles:
  • Focus on the abstract, introduction, and discussion to understand relationships and theoretical justifications; ignore overly statistical details not essential to the theory.
  • Identify core theories and mechanisms that explain why variables relate to organizational deviance.
  • Treat research as iterative; you won’t finish everything in one week, but start with core concepts and expand as you gather more sources.
• When presenting your method, include:
  • The number of items per scale, and which items are reverse-scored.
  • The exact Likert scales used (e.g., 1-5, 1-9) and how scores were computed (sum vs. average).
  • The operationalization of the dependent variable (organizational deviance) with concrete examples (e.g., lateness, reduced performance).
• Data analysis expectations (not deeply statistical here): focus on theory-driven interpretation of relationships rather than statistical details.

Next steps for students

• Start thinking about your two variables early and draft initial hypotheses linking each to organizational deviance.
• If you need help, consult the lecturer to discuss your ideas and ensure they’re well-grounded in theory.
• Prepare to discuss how you would justify chosen variables theoretically and how you would address potential counterarguments or alternative explanations.
• Stay engaged with the live survey data as it becomes available to refine your hypotheses and interpretation.

Key logistical reminders (quick reference)

• 18 variables total; more than 15, as is typical each year.
• All items, scales, and reverse scoring details are on the weekly slides; download them for precise method reporting.
• Data collection window closes in two weeks; the specific date is September ext{ }7.
• Minimum sources: at least 10 references; prioritize foundational and well-cited papers.
• Survey eligibility: 18+ or 17+ if university student; working experience required; psych 20 participants to be excluded from data.
• Use the provided assessment and marketing criteria to guide the write-up and ensure alignment with marking expectations.